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Fiscal Policy for Sustainable Development in Asia-Pacific Gender Budgeting in India Lekha S. Chakraborty
Fiscal Policy for Sustainable Development in Asia-Pacific
Lekha S. Chakraborty
Fiscal Policy for Sustainable Development in Asia-Pacific Gender Budgeting in India
Lekha S. Chakraborty National Institute of Public Finance and Policy New Delhi, Delhi, India
ISBN 978-981-19-3280-9 ISBN 978-981-19-3281-6 (eBook) https://doi.org/10.1007/978-981-19-3281-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
For my mom.
Foreword
The public budget of a country is one of the earliest economic tools that economists and accountants have had available over the years for their theorizing and their analysing. Public budgets became available when the public accounts of countries could be separated from the private accounts of those who ran the countries (kings or other rulers). The early, original budgets were limited in their size and had few explicit objectives to promote. These included national defence, domestic security (with police and justice), some essential public infrastructure, administration, and a few others. Equity objectives generally played very limited if any role in old budgets. The situation started changing in the twentieth century, especially in the second half, when countries became more democratic, and when the pursuit of equity and other social goals progressively entered the public budgets. Access to higher public revenue had also become easier, due to changes in the economic structures and to the growing acceptance of the principle of ability to pay in taxation. These changes made the pursuit of utilitarian objectives more achievable, through public budgets. Budgets became progressively more ambitious in the goals that they promoted. Budgets became also more detailed documents, and generally more complex. Their marksmanship moved from the abstract concept of the “country” to the more specific one of its “inhabitants”, generally defined as nucleuses of families and with some stratifications among
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different classed or categories of citizens. The social-utilitarian objective became progressively more important. As time passed, the past uniformity in objectives of public budget started to give way to new considerations. The need to educate the young, and to increase the countries’ “human capital” directed more budgetary attention to the needs of the young. The lengthening of life expectancy, that increased the share of older components of the populations, directed the allocation of some spending to the protection of the old. The breaking up of large, extended families created increasing public needs to deal with invalids and individuals needing special attention. In countries with individuals from different races, racial equity started to attract attention. In countries with high shares of foreign born, the treatment of immigrants attracted some importance. Finally, the realization that men and women may be subjected to different stresses in most countries, and in some more than in others, could not fail to become an area of interest to the budget. This book is especially focused on the roles that men and women play in the economies of many countries and in the ways in which budgets have ignored or have accommodated those roles. It provides the most comprehensive survey now available of what is known in this area and on what has been achieved so far in several, different countries, including India. “Gender budgeting” has become progressively more common in the world but the author argues that it has not become common enough. Many countries’ budgets continue to implicitly discriminate against women, especially in some countries, and especially in developing countries. In some of these countries, women have often responsibilities within families that demanding but are not officially measured. These responsibilities may include having to get drinking water or fuel for burning from far away sources. Because of these burdens, girls often are not able to attend schools thus making more difficult for them to raise their life incomes. In these cases, public spending that provided families with running water and burning fuel would remove this significant “gender bias”. But such cases would require higher public resources. Thus often difficult choices must be made. The choices must pay attention to gender considerations. The eleven chapters that form this book are full of information on these issues and on attempts by various countries and by some sub-national jurisdictions to deal with gender-relevant issues in their budgets. The
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book provides a lot of statistical evidence and useful discussion of the connection between gender budgeting and the UN sustainable development goals. The book recognizes that the “mechanism design” that is needed to achieve various social goals is often inadequate and needs reforms. Sen’s concern about the many statistically “missing women” in countries such as China and India also attracts some discussion. The book highlights the difference between “ex ante gender budgets” and “ex post gender budgets”, recognizing that inefficiency or even corruption may distort the budgetary interventions away from the original intentions. Australia is mentioned as having been a pioneer in developing a gender-sensitive budget statement. The need for using a “budget lens” is now increasingly recognized and countries are becoming increasingly aware of the need for such lens. The book reports that as many as 90 countries are now pursuing some form of “gender budgeting”. This trend has created an increasing need for statistics that are disaggregated by gender. Such reliable statistics often do not exist. Lekha Chakraborty’s new book is a welcome addition to an area of public finance that is still relatively unknown to many. It is an area that is likely to grow in importance. This book should help in attracting increasing attention to this area. Vito Tazi Former Director, IMF Fiscal Affairs Washington DC, USA
Preface
Fiscal policy is prima facie gender-neutral. But it can turn gender blind due to the socio-economic asymmetries in development across gender. The role of public policy is to ensure “Leave No One Behind” in the journey towards sustainable economic growth. Gender budgeting, as a Public Financial Management (PFM) tool, is about applying a “gender lens” in fiscal policy frameworks to redress gender inequalities by ensuring fiscal transparency and accountability. In 2016, the International Monetary Fund (IMF), for the first time ever, asked its member nations to integrate gender budgeting into PFM. Gender budgeting has reached the world stage when United Nations Secretary-General (UNSG) High-level Panel on Women’s Economic Empowerment in 2016 identified gender budgeting as one of the tools to ensure gender equality. Extraordinary times require extraordinary policy responses. In the times of global uncertainties and the COVID-19 pandemic, it is opportune to unpack what gender-responsive fiscal policy entails. With many governments preparing public finance strategies for the post-pandemic fiscal year, we now have a renewed opportunity to strengthen gender budgeting as an effective PFM tool to redress mounting inequalities. In Asia-Pacific, gender budgeting has evolved as a fiscal innovation, that translates gender-related commitments to fiscal commitments through identified processes, resources, and institutional mechanisms, impacting both the spending and revenue sides of the budget. In a country like
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India, where it is well known that gender discrimination starts even before birth resulting in adverse sex ratios at birth, gender budgeting is a powerful tool to redress gender inequalities. The National Institute of Public Finance and Policy (NIPFP), an independent think tank of the Ministry of Finance, is the pioneering institute to conduct gender budgeting in India. Since 2004, at national and selected subnational levels, gender budgeting has been institutionalized within the Ministry of Finance using NIPFP methodology for preparing the analytical matrices. India is a leading example of sustainable gender budgeting in Asia-Pacific region. Korea has integrated gender budgeting within National Finance Law in 2006, within the legal fiat. In the Philippines, gender budgeting was made mandatory by legally earmarking 5% of all sectoral expenditure on women. However, the “earmarking” can only be a second-best principle of gender budgeting. The fiscal marksmanship—possibility of fiscal forecasting errors—of gender budgeting is a crucial determinant to understand why higher budgetary allocation does not automatically ensure higher public expenditure for women’s empowerment. The overall macroeconomic environment of Asia-Pacific region—especially the procedures that relate to “fiscal rules” and avoiding fiscal austerity—plays a crucial role in ensuring gender equitable outcomes of gender budgeting. I hope my book will interest students, economists, media professionals, and policymakers who are searching for understanding gender budgeting, and how countries can promote greater gender equality through public finance management. New Delhi, India
Lekha S. Chakraborty
Acknowledgements
I would like to thank the National Institute of Public Finance and Policy (NIPFP) for the enabling environment to write this book. I express my gratitude to NIPFP, International Monetary Fund (IMF) and Levy Economics Institute of Bard College, New York for granting me permission to use my selected working papers in this book. I benefitted immensely from my presentations in international meetings—including the American Economic Association Meetings in Atlanta—and from my professional interactions with eminent scholars and policymakers, to write the book. I would particularly like to thank the Governing Board of Management of the International Institute of Public Finance Munich, where I am a Member; the International Working Groups on Gender, Macroeconomics and International Trade; Econometric Society of India and the Research Group on Employer of Last Resort for enabling academic deliberations. I express my sincere gratitude to my mentors and colleagues at NIPFP, Levy Economics Institute, Centre for Development Studies, American University, University of Utah, Uppsala University, Carleton University; IMF, World Bank, and various UN entities where I worked on short stints. I must record my appreciation for my research interns for their help in analysis, at various stages of my book.
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ACKNOWLEDGEMENTS
I express my gratitude to two anonymous reviewers of the book to whom it was sent by the Palgrave Macmillan. I immensely benefitted from their comments. I express my love to my family—particularly my son—for their immense support.
Contents
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Introduction The Macroeconomic Backdrop The Rationale The Analytical Framework Ex Ante and Ex Post Frameworks of Gender Budgeting The Structure References
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Macroeconomic Policy Coherence for Gender Equality in Asia-Pacific Fiscal Policy Stance Effective Fiscal Management and Governance Inequalities in Fiscal Policy Linking Resources to Results: Outcome Budgets Normative Framework and Methodology to Analyse the Fiscal Policy for Gender Equality Monetary Policy Stance Structural Reforms Mapping of Macro Policies in Asia-Pacific Identifying Specific Policy Tools References
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Gender-Budgeting and Gender Equality Outcomes: Evidence from Asia-Pacific Measuring Gender Equality Interpreting Data The Empirical Investigation The Significance to Go Beyond Models References
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Gender Budgeting and the Efficacy of Measuring Unpaid Care Economy Statistical Invisibility of Unpaid Care Economy Time-Use Pattern Across Gender and Geography in India Valuation of Unpaid Care Economy: An Illustration Gender Budgeting: The Link Between Public Investment and Time Allocation References Determining Gender Equality in Fiscal Federalism: Evidence from India Theoretical and Empirical Literature Fiscal Federalism in India: Institutional Details Fiscal Federalism Arrangements and Gender Equality The Empirical Models and Results References Fiscal Decentralization and Ex Ante Gender Budgeting: Case Studies of Selected Countries Including India Fiscal Decentralization and Gender Frameworks Third Tier Institutional Details: Fiscal Devolution Through a Gender Lens Fiscal Decentralization and Local Level Gender Budgeting: Case Studies The Philippines India Kerala Karnataka West Bengal Fiscal Decentralization and Local Level Gender Budgeting in Other Countries: Case Studies
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Morocco South Africa Ethiopia Nepal IMF Government Finance Statistics (GFS): Analyzing “General Government” Data References 7
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Fiscal and Regional Context of Gender Budgeting in Asia Overview of Gender Budgeting in Asia Country-Specific Gender Budgeting Efforts in Asia Pacific Australia Initial Project on Gender Budgeting A Backlash: Office of Status of Women demoted from Prime Minister’s Office Abrupt End to Gender Budget Statements Korea Legal Backing for Conducting Gender Budgeting Institutionalizing Gender Budgeting Gender Budgeting in Infrastructure Local Level Gender Budgeting Challenges Summary of Prominent Gender Budgeting Efforts The Philippines Fiscal Decentralization and Gender Budgeting Bangladesh Sri Lanka Indonesia Pakistan Country-Specific Outcomes Positive Outcomes of Gender Budgeting References Gender Budgeting, as Fiscal Innovation in India Gender Budgeting, as a Fiscal Innovation Integrating Gender in Intergovernmental Transfers Tax Side Gender Budgeting and Tax Incidence Analysis Strengthening Accountability Mechanisms and Capacity Building and Gender Mainstreaming
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Phase 1: Country-Specific Gender Diagnosis and Intergovernmental Fiscal Framework Models Phase 2: Intergovernmental Institutional Design Phase 3: Capacity Building Phase 4: Accountability Mechanisms Public Expenditure Tracking Gender Equality Outcomes Across Indian States References 9
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The Political Economy of Gender Budgeting in India and Fiscal Marksmanship Fiscal Rules and Financing of Deficits in India The Intergovernmental Fiscal Transfers in India, 2021–2022 Applying “Gender Lens” to Union Budget 2021–2022 Fiscal Marksmanship References Gender-Budgeting Outcomes and Public Expenditure Benefit Incidence The Analytical Framework The Public Expenditure Benefit Incidence Analysis (BIA) Methodology Estimating Unit Cost Identifying the Users Aggregating Users into Groups Calculating the Benefit Incidence International Classification of Diseases (ICD)—Benefit Incidence Quintile-Wise Benefit Incidence and Polarization Ratio References COVID-19 Context and the Way Ahead Constraints of Rules-Based Policy Space Obsession with “Economic Growth” Frameworks Fiscal Sustainability in Low Interest Rate Regime Strengthening Fiscal Marksmanship Innovative Financing of Deficits Incorporating Unpaid Care Economy into Macro Policy
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Acknowledging Intersectionality Issues in Gender Budgeting Fiscal Decentralization: Move Ahead from “One Size Fits All” Gender Budgeting Link Between Fiscal Policy and Gender Equality Outcomes Public Expenditure Tracking and Fiscal Incidence Analysis Measuring Gender-Aware Human Development Outcomes Second Generation Reforms of Gender Budgeting Integrating Gender in Intergovernmental Fiscal Mechanisms Gender Budgeting and Feminization U Strengthening Gender Budgeting on Taxation Side Fiscal Transparency and Accountability Through Gender Budgeting Political Will for Sustainable Gender Budgeting as PFM References
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Abbreviations
AAAA ADB AEA BCC BEE BIA CAG CEDAW CEE CGE DBT DILG EPWP EWR FC FR FSLRC GAD GDI GDI GE GEAR GEM GFS GII
ADDIS ABABA ACTION AGENDA Asian Development Bank American Economic Association Budget Call Circular Black Economic Empowerment Benefit Incidence Analysis Comptroller and Auditor General Convention on the Elimination of All Forms of Discrimination Against Women Commission of Employment Equity Commission of Gender Equality Direct Benefit Transfers Department of Interior and Local Government Expanded Public Works Programme Elected Women Representatives Finance Commission Fertility Rate Financial Sector Legislations Reforms Commission Gender and Development Gender-Related Development Index Gender Development Index Gender Equality Growth, Employment and Redistribution Gender Empowerment Measure Government Finance Statistics Gender Inequality Index xxi
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ABBREVIATIONS
GST HDI HDR ICD IGFT IHDI ILO IMF JMC KWDI LFPR LGC LGU MGNREGA MMR MPCE MTFF MWCD NCRFW NIPFP NITI NSO NSS OECD OSW PEFA PFM PSBR RGI RMSE SDG SDP SE SFC SGSY SHG SNA SPRSM SRS TFP TLLSS TOR TUS
Goods and Services Tax Human Development Index Human Development Report International Classification of Diseases Intergovernmental Fiscal Transfers Inequality Adjusted Human Development Index International Labour Organisation International Monetary Fund Joint Monitoring Committee Korean Women’s Development Institute Labour Force Participation Rate Local Government Code Local Government Unit Mahatma Gandhi National Rural Employment Guarantee Act Maternal Mortality Ratio Monthly Per Capita Expenditure Medium Term Fiscal Framework Ministry of Women and Child Development National Commission on the Role of Filipino Women National Institute of Public Finance and Policy National Institution for Transforming India National Statistical Organisation National Sample Survey Organisation for Economic Cooperation and Development Office of Status of Women Public Expenditure Financial Accountability Public Financial Management Public Sector Borrowing Requirement Registrar General of India Root Mean Squared Error Sustainable Development Goal State Domestic Product Secondary Education State Finance Commission Swarnajayanti Gram Swarozgar Yojana Self Help Group System of National Accounting Strengthening Poverty Reduction Strategy Monitoring Sample Registration System Total Factor Productivity Timor-Leste Living Standards Survey Terms of Reference Time Use Survey
ABBREVIATIONS
UBI UDAY UN ESCAP UNDP UNIFEM UNRISD UNSD VAT WBI WCP WER WHO
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Universal Basic Income Ujjwal Discom Reassurance Yojana United Nations Economic and Social Commission for Asia and the Pacific United Nations Development Program United Nations Development Fund for Women United Nations Research Institute for Social Development United Nations Statistical Division Value Added Taxes Women’s Budget Initiative Women’s Component Plan Women Elected Representatives World Health Organisation
List of Figures
Fig. 3.1
Fig. 3.2
Fig. 3.3
Fig. 3.4
Fig. 3.5
Fig. 3.6 Fig. 9.1
Fig. 10.1
Fig. 10.2
Gross secondary enrolment ratio in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates) Under 5 child mortality in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates) Maternal mortality ratio in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates) Labour force participation rate in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates) Women in national parliaments in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates) GDI, time consistent version (Source Authors’ estimates) Distribution of the Gender Budget in the Total Budget, India (Source [Basic Data], Expenditure Budgets Union Budget 2021–2022, Government of India [2019]) Concentration curves, public expenditure incidence, and targeting: Pictorial representation (Source Davoodi et al. [2003]) Gender Differential in Benefit Incidence: All ICD Combined (Source Government of India [2015], National Sample Survey 75th Round on Health)
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Gender Differential in Benefit Incidence: Certain infectious and parasitic diseases (ICD-I) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Neoplasms (ICD-II) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism (ICD-III) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Endocrine, nutritional, and metabolic diseases (ICD-IV) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Mental and behavioural disorders (ICD-V), and Diseases of the nervous system (ICD-VI) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the eye and adnexa (ICD-VII) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the ear and mastoid process (ICD-VIII) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the circulatory system (ICD-IX) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the respiratory system (ICD-X) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the digestive system (ICD-XI) (Source Government of India [2015], National Sample Survey 75th Round on Health)
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Gender Differential in Benefit Incidence: Diseases of the skin and subcutaneous tissue (ICD-XII) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the musculoskeletal system and connective tissue (ICD-XIII) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Diseases of the genitourinary system (ICD-XIV) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Pregnancy, childbirth and the puerperium (ICD-XV), and Certain conditions originating in the perinatal period (ICD-XVI) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Injury, poisoning, and certain other consequences of external causes (ICD-XIX) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: External causes of morbidity and mortality (ICD-XX) (Source Government of India [2015], National Sample Survey 75th Round on Health) Gender Differential in Benefit Incidence: Factors influencing health status and contact with health services (ICD-XXI) (Source Government of India [2015], National Sample Survey 75th Round on Health)
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List of Tables
Table 3.1 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8 Table 4.9 Table 4.10 Table 4.11 Table 4.12
Determinants of GDI, GII, and sectoral spending: panel estimates Time allocation in SNA and Non-SNA, India 2020 Distribution (%) of time use into SNA and Non-SNA, India 2020 Age-disaggregated time allocation in SNA and Non-SNA in India, 2020 Age-disaggregated distribution (%) of time allocation in SNA and Non-SNA, India 2020 Time allocation of men and women in a day in different activities in India, 2020 Time allocation by men and women of different levels of education in India, 2020 Time allocation in different activities by geography, 2020 Distribution (%) of time, by geography and gender, in India, 2020 Percentage of men and women participating in different activities (usual principal activity status) Time allocation by women and men, selected states of India (weekly average time in hours) Distribution (%) of time use in SNA and Non-SNA: Selected states in India Valuation of unpaid care economy: Selected states of India
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Table 4.13 Table 4.14 Table 5.1 Table 5.2
Table 5.3
Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table Table Table Table Table Table
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Table 8.3 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 9.7 Table 9.8 Table 9.9
Time-use pattern by men and women in water sector (weekly average time in hours) Econometric Link between Infrastructure and Time Allocation Descriptive statistics Impact of intergovernmental fiscal transfers on gender equality, with lagged gender budgeting dependent variable: GMM estimates Impact of IGFT and gender budgeting on fiscal spending, with lagged de-pendent variable—GMM estimates Criteria of gender responsive budgeting and scores in Nepal General government finance: Expenditure (% of GDP) by functions of government, IMF GFS 2019 General Government Finance: Expenditure (% of GDP) by Economic Classification, IMF GFS 2019 General Government Finance: Revenue (% of GDP), 2019 Fiscal context of gender budgeting in Asia Legal Fiat of Gender Budgeting Revenue-Side Gender Budgeting Institutionalizing Gender Budgeting in Korea Phases of gender budgeting in India Gender Inequality Index (GII) across Indian States/Union Territories, 2017–2018 HDI and GDI across Indian States/Union Territories, 2017–2018 Levels of deficit (Rs. crores) Sources of Financing Fiscal Deficit (Rs. crores) The composition and fiscal marksmanship of revenue receipts Anatomy of revenue expenditure Intergovernmental fiscal transfers—conditional and unconditional Part A: Specifically Targeted programmes for Women in Union Budget 2021–2022, India Part B: Sectoral Composition of Gender Budgeting, 2021–2022 Fiscal marksmanship: The Sources of Fiscal Forecasting Errors Fiscal marksmanship of Gender Budgeting: Part A
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LIST OF TABLES
Table 9.10 Table 10.1 Table 10.2 Table 10.3 Table 10.4
Table 10.5 Table 10.6
Fiscal Marksmanship of Part B Allocations of Gender Budgeting, 2020–2021 WHO International Classification of Diseases (ICD) to Indian National Sample Survey Mapping Unit Utilized in Health Sector: As per income quintiles across gender, India 2019 Average medical expenditure for Ambulatory Health Services across Indian States, 2019 (in Rs.) Disease-specific Morbidity: Unit Utilized Pattern of Hospitalization across Plausible ICD-10 Mapping, India 2019 Polarization Ratio Quintile-wise Behavioural Access to Health Care in Rural and Urban India Across Gender
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CHAPTER 1
Introduction
Extraordinary times require extraordinary policy responses. In the time of COVID-19 pandemic, with the widespread lockdowns, women have disproportionately borne the socio-economic brunt of the pandemic. With many governments preparing public finance strategies for the postpandemic fiscal year, we now have a renewed opportunity to strengthen gender budgeting as an effective public finance management tool to redress these mounting inequalities (Polzer et al., 2021; Sayeh et al., 2021). Gender budgeting is a fiscal innovation, encompassing all phases of public financial management (Chakraborty, 2014). Ideally, gender budgeting is an approach to fiscal policies and administration that translates gender-related commitments into fiscal commitments through identified processes, resources, and institutional mechanisms, impacting both the spending and revenue sides of the budget. Prima facie, the fiscal policies may appear to be gender-neutral. It can turn gender-blind due to differences in the socially determined systemic roles played by women and men. As a consequence, gender-neutrality of fiscal policies can turn to gender blindness (Elson, 2000; Elson & Cagatay, 2000). This is due to the fact that women and men are at asymmetric levels of development on the socio-economic scale. The UN’s COVID-19 Global Gender Response Tracker revealed that more than a thousand fiscal policy measures have been implemented by different countries—as part of fiscal stimulus packages—to tackle the widening gender © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_1
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inequalities. However, adopting such policies is only a partial approach to tackling gender inequalities. This is primarily because the fiscal stimulus packages are short run in nature. Ideally, there should be a coherent longterm macroeconomic policy framework to integrate gender concerns, and to translate the gender equality commitments into fiscal commitments. This is the core of gender budgeting, to ensure a sustained fiscal space for gender equality through transparency and accountability. Gender budgeting is emerging as an important Public Financial Management tool to analyze the efficacy of the fiscal policies on gender equality. Gender budgeting does not mean making separate budgets for women nor is it confined to the analysis of earmarked funds for programmes exclusively targeted at women within budgets (Chakraborty, 2016a; Kolovich, 2018; Stotsky, 2016). It refers to an analysis of the entire budget through a gender lens to identify gender-differential impacts and translate gender commitments into budgetary commitments (Ça˘gatay et al., 1995; Cagatay et al., 2000). Integrating gender in fiscal policy enhances transparency and accountability. Gender budgeting is an analysis of budgets to ascertain the relative benefits (or losses) derived by each gender from a particular fiscal programme/project. Gender budgeting has reached the world stage when the United Nations Secretary General’s High-level Panel identified gender budgeting as one of the specific policy tools for Women’s Economic Empowerment in 2016. The commitment of IMF in 2016 for the first time ever to conduct gender budgeting within the Public Financial Management (PFM) also strengthen the efficacy of gender budgeting on gender equality outcomes.
The Macroeconomic Backdrop The macroeconomic uncertainty in times of the COVID-19 pandemic is hard to measure. The economic stimulus packages are short run in nature and the “normalization” process will begin by phasing out the COVID-19 stimulus announcements. In such contexts, long term Public Financial Management (PFM) tool like gender budgeting has significance to correct the exacerbating gender inequalities. Gender-budgeting frameworks also push the frontiers ahead of the economic growth paradigm. The economic growth per se will not “trickle down” to better human development outcomes. The macroeconomic frameworks are rules-based across countries— both for fiscal and monetary stance. The monetary stance is based on
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inflation targeting rules—where the policy rates are pegged on the basis of deviation of inflation anchor from inflationary expectations and the output gap. The inflationary expectations and output gap are unobserved variables. The inflationary expectations are constructed on the basis of expectations surveys. The inflationary expectations data is gender neutral. The output gap is the difference between potential output and actual output. The potential output is not inclusive of the economic activity outside the purview of Systems of National Accounts (SNA). The potential output is constructed by decomposing the output into trends and cycles. The unpaid care economy is not taken into consideration while constructing the potential output. Such underestimates of potential output are generated through econometric methodologies—mostly filters—which eliminate the cyclicality elements of GDP and arrive at the potential component using the trend elements of the series. If the fastest and smartest way to increase the potential GDP is by incorporating the economic activity done by women, conscious public policies related to care economy infrastructure are crucial. Economists and policymakers use the variable “output gap” to capture the macroeconomic uncertainties. This deviation between potential output and actual output is a standard representation of a “cycle”. It is based on business cycle theories. However, the business cycle always is not a “cycle” (Aguiar & Gopinath, 2007). When the COVID-19 pandemic and other macroeconomic crises tend to “permanently” push down the level of a country’s GDP, it is inappropriate to assume that output will bounce back to prior-pandemic levels. The hysteresis (the dependence of economic path on history) in analysing the output dynamics in COVID-19 pandemic crisis is significant for designing appropriate fiscal and monetary policies to tackle the COVID-19 pandemic. This is because of the persistence of sluggish growth and weak macroeconomic recovery. The assumption that recessions are followed by quick rebounds is not always correct. The economic recovery can be uneven if fiscal and monetary policy stances do not integrate gender-aware human development components into the policy processes. The economic stimulus packages have two components—instantaneous firefighting packages and structural reforms. It is important to apply a “gender lens” in both these components of economic stimulus packages to pre-empt exacerbating gender inequality outcomes. The central banks so far have not integrated a “gender lens” into the monetary policy reaction function. However, the debate on whether
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climate change can be part of monetary policy has begun. Many central banks have started assessing the climate change risks and uncertainties through green stress tests of investment decisions, as these climate change related risks can in turn affect the financial stability (Chakraborty, 2022). The significant policy tool of the central bank is policy rates. During the times of COVID-19 pandemic, the central banks have kept the policy rates lower for the sustained growth recovery process. However, with mounting inflation against the backdrop of Russia’s war in Ukraine and the energy price volatility, central banks have huge pressure to raise the interest rates. If the central banks “bite the bullet” and hike the interest rates, it can dampen the growth recovery process (Roubini, 2022). If central banks do not increase the interest rates, it can lead to the deanchoring of inflationary expectations and lead to the reputation risk of the central banks. With zero lower bound and negative real interest rates, the monetary policy has proved inefficacious as a countercyclical policy tool to reset the economy to pre-crisis growth levels. The fiscal re-dominance at the same time, though desirous, has been bound to the fiscal austerity wave and tight fiscal rules. The world nations will miss the chance to reset the economy to the pre-crisis levels in terms of growth and gender-aware human development, if fiscal policy space does not remain accommodative in the times of pandemic crisis. Fiscal rules insist that the level of fiscal deficit to GDP ratio needs to be maintained at 3 per cent. However, there is a fundamental rethinking of the efficacy of fiscal rules against the backdrop of a pandemic (Chakraborty & Harikrishnan, 2022). High public debt has no fiscal costs if the real rate of interest is not greater than the real rate of growth of the economy (Blanchard, 2019). High public debt is not catastrophic if “more debt” can be justified by clear benefits like public investment or “output gap” reduction. Blanchard (2019) highlighted the “hysteresis effects” (the persistent impact of short-run fluctuations on the long-term potential output) and suggested that a temporary fiscal expansion during a contraction could even reduce debt on a longer horizon. There is increasing recognition of the fact that gender-aware human capital formation and physical infrastructure have suffered from fiscal consolidation measures. In the context of emerging economies, public investment is a significant determinant of “crowd-in” private corporate investment (Chakraborty, 2016b, 2022). If we are worried about a “bad equilibrium”, it is better to have a “contingent fiscal rule” (which may not need to be used) rather than steady fiscal consolidation.
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If the path towards fiscal consolidation is through expenditure compression than tax buoyancy, the quality of fiscal consolidation will suffer. The financing pattern of fiscal deficits also need to be analysed to understand the efficacy of gender budgeting. There is a transition in the financing pattern of deficits from seigniorage financing (monetized deficits) towards bond financing. However, there is limited evidence on the earmarking of market borrowings towards specific sustainable development goals. Green bonds—earmarking a portion of sovereign debt bond towards green energy infrastructure—is increasingly getting attention. However, the “gender bonds”—as a transformative financing for gender equality goals—need more calibrated processes. There is increasing attention towards money financing of fiscal programmes. However, due to its inflationary potential, governments have been reluctant to resort to monetary financing of fiscal deficits. However, if the real rate of interest is above the real growth of the economy, public debt may become unsustainable. In such situations, the eventual monetization of deficit is crucial. A finite money financing of fiscal programmes—for a judicious mix of specific fiscal programmes like gender budgeting, Employer of Last Resort (ELR) policies—where the government guarantees jobs; and targeted cash transfers to people in lowincome quintiles to avert the livelihood crisis—is significant in the times of macroeconomic uncertainties. Fiscal policy has a significant role to catalyse aggregate demand in times of crisis. The assumption that demand shocks have only a transitory impact on the economy in the times of COVID-19 pandemic needs a relook. Even demand shocks can have a permanent impact on output. When there are no clear economic cycles, especially when the drop in GDP is a “permanent scar” rather than a transient deviation, the role of fiscal and monetary policy as counter-cyclical policy tools might not operate to help the economy to rebound to a prior-crisis growth path. Economic cycles are defined as a succession of crises that followed periods of prosperity, though these peaks and troughs do not follow a given frequency or periodicity. With the persistence of cyclicality, the economy will not rebound to prior pandemic levels of economic growth. This persistence of cyclicality are the permanent “scars” left by COVID-19 pandemic. Unless fiscal and monetary policies incorporate these aspects, the impact of economic stimulus packages to tackle the pandemic will be partial. The predominant form of pandemic responses was in the form of liquidity infusion.
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However, credit-related economic stimulus packages have limited multiplier effects (Stiglitz & Rashid, 2020). If there is no corresponding growth in the economy, a huge credit infusion can accentuate nonperforming assets. From a gender perspective, the uneven access to credit is a matter of concern. Lowering of interest rates by the monetary policy authorities have made credit cheaper for boosting the investment. However, from a gender perspective, in the debate on cost of credit versus access to credit, it is the latter that matters more for women. Access to formal financial systems has become tough for women due to a lack of collateral. The financial inclusion has happened on a limited scale due to peer monitoring models through self-help groups. However, when the markets are uncertain, the pressure of credit repayment can compel women to engage in Ponzi finance with the indigenous money lenders at higher rates of interest.
The Rationale The dual rationale for integrating a gender lens into macroeconomic policy are its equality and efficiency dimensions. Where there is increasing recognition that problems of inequality cannot be resolved by trickledown effects of economic growth, the concerns about gender inequality need to be built into the macroeconomic policy framework. Apart from the “social justice” and “human rights” dimensions, gender equality can benefit the economy through efficiency gains (Lahiri et al., 2002; Sharp, 2003). From an efficiency perspective, what is important is the social rate of return on investment in women, which can be shown in some cases to be greater than the corresponding rate for men (Elson, 1999). Gender budgeting, within a rights-based approach, is increasingly recognized as a tool to address gender discrimination (Elson, 2006). A rightsbased approach, among other things, looks at the resource requirements (budgets) for human development. A “human rights” approach provides values against which to assess budgets; it assists in choosing between different budgetary and policy options and strengthens the demand for budget transparency and fiscal accountability. Gender budgeting is also based on the premise of ensuring transparency in the budgetary allocation for women, protecting these provisions from re-appropriation and thereby enhancing accountability (“voice”).
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Economic growth is often cited as an outcome of reducing gender inequality (SDG 5), which serves to close inefficient gender gaps in workforce participation, education, and health (Berik, 2006; Berik et al., 2009; Dollar & Gatti, 1999; Klasen, 1999, 2002; Seguino, 2008). Another motivation for SDG5 (gender equality) is its perceived potential to promote equitable development, distinct from economic growth. There are two facets to this motivation: at a basic level, women and girls tend to suffer greater disadvantages across a range of social and economic indicators, therefore alleviating these development disparities through gender-budgeting programmes has been seen as a valid development end in itself (Chakraborty et al., 2017). Secondly, policymakers and academics have long highlighted the value of gender equality as a precursor to, or tool for promoting, economic development more broadly (Chakraborty et al., 2017; Palmer, 1995; Sen, 2000; World Bank, 2011). Once the policy commitment is set, the success of these attempts becomes crucial for economic “institutions”.
The Analytical Framework The analytical framework of gender budgeting rests on the role of the government to design an ideal “mechanism design” for better gender equality outcomes. Intertemporally, the role of government has widened from the strict confinements of security, law and order functions of the State to redistributive justice and equity issues. There is an increasing recognition of the role of institutions in analysing the processes of growth and financing sustainable development goals (SDGs). From this perspective, the gender aware human development has become a function of fiscal policy. Theoretically, an ideal mechanism design is based on the ability of a government to achieve simultaneously Pareto optimality, incentive compatibility (of what government provides and what citizens desire from the government) and a balanced budget. However, as Hurwicz (1952) in his work on mechanism design had rightly pointed out that the simultaneity of these three conditions is unattainable, leave alone the chances of any two of these conditions likely to be attainable. The government, as a mechanism designer, at the outset, if aware of the set of policy priorities required for optimal outcomes can subsequently design mechanisms for achieving it. Unpacking the algorithms, researchers have analysed the existence of any “Wicksellian links” in the
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economy. The Wicksellian links suggest that the unit of tax paid by the citizens and the unit of satisfaction derived by the citizens from the public provisioning are interconnected. If not, the Wicksellian connection breaks. Empirical evidence suggests that the Wicksellian links in the context of emerging and developing economies are weak. This evidence is based on the empirical literature on tax evasions and non-compliance with taxes by the citizens. The citizens prefer to reveal their demand from public provisioning of goods “strategically” than “sincerely” to avoid paying taxes. When citizens reveal their preferences as more “strategic than sincere”, the public financing of goods and services becomes difficult. The Lindahl–Wicksell mechanism had suggested an atomized taxation regime to break this policy uncertainty. These atomized taxes are also to solve the mechanism design issues. The Lindahl–Wicksell mechanism of “atomized taxes” works as follows—increase the tax rate for those who reveal a strong demand and decrease the tax rate for those who reveal a weak demand, so that in the course of time, the demand will increase from those who are taxed less and the demand will decrease from those who are taxed more and an equilibrium mechanism design can be theoretically attained. However, an atomized taxation regime cannot be an ideal mechanism design for financing gender equality goals. The moment a citizen reveals his/her preferences strategic than sincere—for instance, gender aware human development financing is of no priority—the public financing of this priority rise to a level of devastating dimension. While these algorithms of mechanism design remained inconclusive, the narratives that have catalyzed the notion of institutionalizing gender budgeting are based on the premise that institutions are the “rules of the game” in a society and these are the humanly devised constraints that shape human interaction (North, 1991). Acemoglu and Robinson (2013) argued that institutions, and they alone, determine the prosperity of a nation. They emphasized the significance of “inclusive economic institutions” that enforce property rights and create a level playing field in a pluralistic manner. Gender budgeting from that perspective can be a transformative financing for gender equality (Chakraborty, 2016c). Maskin (2008) in his Nobel prize lecture “Mechanism Design: How to Implement Social Goals?” Narrated that mechanism design begins by identifying desired outcomes (goals)—where he asks whether economic institutions (mechanisms) could be designed to achieve social goals—if so, what forms would institutions take? This is quite contrary to the “positive” approach that usually macroeconomists prescribe which excludes
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gender development-conscious economic growth (Chakraborty, 2016c). The government is the mechanism designer which chooses the institution (procedure, mechanism or game) that determines outcome (gender equality). The outcomes are context-dependent and depend on the choice and priorities of the government. Why explorations on the role of mechanism design (institutions, procedures and public policies) in analysing the “endemic social constructs” including patriarchy remain elusive? What makes gender budgeting compelling? Recall the debate set off by Amartya Sen when he claimed that millions of women were “missing”. This is a human catastrophe. There is a need to analyze the role of public policy and institutions in correcting these blatantly oppressive prejudices that run deep in the society and results in female survival disadvantage, as well as the role of institutions in upholding the “right to life” for girl children and women (Chakraborty, 2016c). Obvious things are often the most invisible. Surpassing the blatant reality, mainstream economists have always searched for “economic reasons” for integrating gender into macroeconomic policies for enhancing growth (Chakraborty, 2016c). On the other hand, economic growth per se does not gender equality outcomes. The relationship between gender equality and economic growth is an asymmetrical one (Kabeer & Natali, 2013). The dynamic interaction between the statistically invisible care economy segment of the economy, viz., the household and community production of non-marketed goods and services included as per the United Nations Statistical Division (UNSD) revisions in the Systems of National Accounts (SNA) 1993, and that of the market economy have marked the market-oriented foundations of engendering macroeconomic policies (Chakraborty, 2016c). These dynamics capture the intra-household intensity and allocation of time between the dual sets of economic activity. In recent years, “time deficits” in the invisible care economy due to the deficiency in public infrastructure investment and related public policies itself have become the prominent research agenda globally. The macroeconomic policies for gender development—especially gender budgeting as “institutional reforms”—have started earning recognition. The government can announce a national finance law mandating that choice. Gender budgeting has been mandated by law in many countries including Mexico (Oaxaca), Korea and the Philippines. In Oaxaca, gender-disaggregated taxation policies were mandated by law. In Korea,
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National Finance Law incorporated Articles on gender budgeting, as a Public Financial Management (PFM) tool (Chakraborty, 2016a). In the Philippines, gender budgeting was mandated by law to earmark a specific component of developmental budgets for gender development projects, which they referred to as Gender and Development (GAD) budgets. Budget Call Circulars have been used in several countries to make gender budgeting mandatory (Budlender, 2015). An “ought-to-be” reforms package may be designed by the highest policymaking body with gender budgeting as one of the high policy priorities (Chakraborty, 2016c). Unpacking the social content of macroeconomic policies is pertinent for rapid economic growth. Right institutions and innovative tools should be adopted to strengthen the “gender lens” of public spending decisions and how gender differential outcomes of fiscal policy are measured. The role of the Ministry of Finance in owning such gender equity considerations from a fiscal policy perspective is significant. However, the uncertainties involved in fiscal innovation, the inability of the economic agents to clearly visualize the appropriate measures, data paucity, and the efficacy of the new institutional mechanisms to take it to logical outcomes were the formidable challenges posed to the gender-budgeting process (Chakraborty, 2016c). While social mores cannot be fully transformed by fiscal fiats, a proactive mechanism design by the State is called for. Here, the crucial question that confronts one’s mind is, “to design policy for what?”—for “economic growth” or for human development-conscious growth? (Chakraborty, 2016c). Ex Ante and Ex Post Frameworks of Gender Budgeting The analytical framework for preparing gender budgeting can be broken down into: (a) ex ante gender budgeting, in which the needs of the women are identified first and then incorporated into the budget and (b) ex post gender budgeting, in which the existing budget is analysed through a gender lens. Ex ante gender budgeting is articulated as the identification of gender needs in the planning process which is essential for the budgeting (Chakraborty, 2014). Ex ante instruments include gender-budget statements (e.g. in gender needs assessments) and policies such as budget allocations for specific sectors (Polzer et al., 2021). Governments employ concurrent policies and tools when they consider a gender perspective during their resource allocation, for example through
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programme-based budgeting or tracking the progress of gender spending. Ex post approaches include tools (e.g. spending reviews and gender audits) or focus on policy analyses (e.g. causes of gender gaps) (Polzer et al., 2021). Comprehensive gender-budgeting systems encompass all three stages of the budgeting process. An ex post gender-budget analysis begins with the identification of three categories of public expenditure: (i) Expenditure specifically targeted to women and girls (100 per cent targeted for women); (ii) Pro-women allocations; which are the composite expenditure schemes with a women component (that is, a scale of 100 to 30—at least 30 per cent targeted for women); and (iii) Mainstream public expenditures that have gender-differential impacts (that is, a scale of 0–30). It is relatively easy to identify the specifically targeted programmes for women across ministries from the Expenditure Budget documents (Chakraborty, 2016a). But the challenge is that discerning what component of mainstream budget programmes has a “pro-women” or gender-equality impact is not easily done from simple perusal of the budget documents. The ex post gender budgeting can be extended to gender-disaggregated benefit incidence analysis. The public benefit incidence (BIA) analysis is one of the tools identified for gender budgeting. BIA is a relatively simple and practical method for estimating the distributional impact of public expenditure across different demographic and socio-economic groups. BIA can identify how well public services are targeted to certain groups in the population, across gender, income quintiles and geographical units (Austen et al., 2013; Budlender et al., 2002; Demery, 2000). Apart from public expenditure incidence analysis, Elson (1999) described some other tools for conducting gender budgeting, which include gender-aware policy appraisal of macroeconomic strategy and Medium-Term Economic Policy Framework; gender-disaggregated beneficiary assessments; sex-disaggregated analysis of the impact of the budget on time use; gender-aware Medium-Term Economic Policy Framework; gender-aware Budget Statement; and tax incidence analysis. A gender-aware policy appraisal of the overall macroeconomic strategy and Medium-Term Economic Policy Framework depends on the macro-fiscal strategy and the sustainability of public debt. The sustainability of public debt is a condition where the real rate of interest is not greater than the real growth of the economy (Chakraborty, 2016b). If the fiscal consolidation path takes place through expenditure compression than through
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tax buoyancy, the human development related expenditure may decline. This expenditure compression path affects gender budgeting negatively. The gender-disaggregated beneficiary assessment is a qualitative methodology by which the citizens are asked to assess how far fiscal policies are beneficial for them, as they perceive them through opinion polls, attitude surveys, group discussions or interviews. This participatory budget process offers inferences for redistribution and more budget accountability. The gender-disaggregated impact analysis of budget on time use is based on the realization that women contribute disproportionately larger amounts of their time to unpaid care economy activities. Therefore, the fiscal policies relate to tax credits for child care, parental leave, child benefits and single-parent allowances have positive impacts on the unpaid care economy. Women had to travel greater distances to collect fuel, and therefore integrating gender budgeting in energy sector by providing clean fuel to poor income households can impact positively their health status and time stress. The gender-aware Medium-Term Economic Policy Framework is used to assess the impact of economic policies on women, including both fiscal and monetary policies. This is a useful tool in times of pandemic to assess the impact of economic stimulus packages on women and to design a medium-term strategy. Linking policy, planning and budgeting, the medium-term economic policy framework usually for a three-year rolling budget, describes a government’s policy goals, explains the economic scenario within which those goals are being addressed, and focuses on the resource requirements. The integration of gender analysis into the medium-term budget process goes beyond impact analysis of economic policies, as it is linked to the principles of participatory budgeting. A gender-budget statement is prepared by the government by applying a gender lens to the budget and identifying the intensity of the gender component in public expenditure. For instance, in India, Gender Budget Statements have been released since 2005–2006 including the specifically targeted programmes for women, and the gender components in mainstream spending. This is mandated through Budget Circular across countries. Gender budgeting is not confined to public expenditure analysis. It is also applicable to taxes at various levels of government and intergovernmental tax transfers—both conditional and unconditional fiscal transfers (Anand & Chakraborty, 2016; Chakraborty, 2021; Chakraborty & Singh, 2017; Stotsky, 2021). Global income taxes are typically a source of gender bias, in the countries where couples filing joint returns incur a greater tax
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liability than they would if they filed as individuals (Grown & Valodia, 2010). The indirect taxes may seem to be gender-neutral, however, they can have significant gender-differential impacts based on the household income and the consumption patterns (Chakraborty et al., 2010). Nature resource taxation can have gender-differential impacts. If a portion of natural resource taxes are not earmarked for the human development of the regions they are extracted from, it can accentuate inequalities.
The Structure The book is organized into 11 chapters. Chapter 2 analyses how macroeconomic policy coherence is closely linked to achieving gender equality in the context of Asia Pacific. Specifically, the chapter attempts to identify the significant constraints in the macro policymaking to integrate gender perspectives. There is a transition in the macro policymaking from discretion to rules. Integrating gender perspectives within a rules-based framework is challenging. These constraints in the monetary and fiscal policies are analysed in the chapter. How policy tools can be used in the region to integrate “Leave No One Behind” (LNOB)? An inventory analysis of these policy imperatives is captured in the chapter. Economic growth per se cannot capture the human development outcomes. Measuring gender-aware human development is challenging. Chapter 3 provides the measurement issues related to gender-aware human development outcomes and focusses on establishing the analytical links between macro-fiscal policy and the gender equality outcomes, in the context of Asia Pacific countries. It provides the macroeconomic channels through which these links are established. The statistical invisibility of care economy work—especially the unpaid or unmonetized work in the household—is a matter of concern. Genderbudgeting frameworks provide significance to the efficiency and allocation of time spent in the care economy sector. Using Time Use Survey 2020 in India, Chapter 4 presents an analysis of gender-disaggregated time allocation under SNA (Systems of National Accounts) and Non-SNA. The chapter also provides an overview of how to use macro-fiscal policies— in particular the policies related to public infrastructure—to minimise the private costs. From a public finance perspective, gender-budgeting analysis often rests on the assumption that mainstream expenditures, such as public infrastructure, cannot be gender-partitioned. However, analysis
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in Chapter 4 reveals how a gender lens can be applied to infrastructure investment decisions. Intergovernmental fiscal transfers (IGFT) are, in theory, neither good nor bad for tackling gender inequalities. The asymmetry in revenue and expenditure assignments leads to vertical and horizontal imbalances in fiscal federalism. Chapter 5 analyses the plausibility of incorporating gender criteria into the tax transfers which are designed to redress such vertical and horizontal imbalances. The principle of subsidiarity—which emphasises that the policy decisions can be efficiently taken at a level of government closest to the people—is crucial for conducting gender budgeting. Chapter 6 discusses selected local level fiscal decentralisation and gender-budgeting experiments. The feminization of local governance at the third tier may alter the public expenditure decisions—through gender-budgeting experiments—that correspond more closely to the revealed preferences of women. Gender budgeting is a fiscal innovation. A fiscal innovation encompasses four distinct phases—model building and knowledge networking, setting up institutional mechanisms, strengthening capacity building and ensuring accountability mechanisms. The gender-budgeting efforts in the Asia-Pacific, within the Public Financial Management frameworks, are captured in Chapter 7. The Ministry of Finance played a significant role in the sustainability of gender-budgeting experiments. India is a leading example of gender budgeting, integrating gender budgeting in Budget Circulars, Expenditure Budgets, and the Outcome Budget (Stotsky, 2021; UNDP, 2010). Chapter 8 reveals the path of gender budgeting in India covering those attempts in public expenditure, taxation and intergovernmental fiscal transfers. The National Institute of Public Finance and Policy (NIPFP), an independent research institute of the Ministry of Finance—the pioneer in gender budgeting in India—provided the analytical matrices to conduct gender budgeting in national and subnational governments of India. Gender budgeting is not a technocratic exercise. It has political economy contexts. Chapter 9 analyses the political economy of gender budgeting using Union Government 2021–2022 data through a gender lens, incorporating fiscal marksmanship analysis. Fiscal marksmanship analysis captures the extent of errors in budgetary forecasting. Chapter 10 analyses the distributional impact of public expenditure across income quintiles on women, based on public expenditure benefit
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incidence analysis. The International Classification of Diseases (ICD) codes are used to map the National Sample Survey 2019 data on health sector incidence across income quintiles, gender and geography. Chapter 11 concludes and suggests the way forward.
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Chakraborty, L. (2022). Union budget 2022: Fiscal-monetary interface and green bonds, 57 (13), Economic and Political Weekly. Chakraborty, L., & Singh, Y. (2017). Fiscal policy, as the employer of last resort: The gender differential impacts of MGNREGA in India, (Working Paper No. 210). National Institute of Public Finance and Policy. Chakraborty, L. S., & Harikrishnan, S. (2022). COVID-19 and fiscal-monetary policy coordination: Empirical evidence from India (Working Paper 1002). Levy Economics Institute of Bard College. Chakraborty, L., Marian, I., & Yadawendra, S. (2017). Effectiveness of gender budgeting on gender equality outcomes and fiscal space: Evidence from Asia Pacific. (GRoW Research Paper WP 2017–09). McGill University. Chakraborty, P., Chakraborty, L., Karmakar, K., & Kapila, S. M. (2010). Gender equality and taxation in India: An unequal burden? In C. Grown, & I. Valodia (Eds.), Taxation and gender equity: A comparative analysis of direct and indirect taxes in developing and developed countries (pp. 94–118). Routledge. Demery, L. ( 2000). Benefit incidence: A practitioner’s guide. Poverty and Social Development Group. The World Bank. Dollar, D., & Gatti, R. (1999). Gender inequality, income, and growth: Are good times good for women? World Bank Policy Research Report on Gender and Development, (Working Paper Series 1). World Bank. Elson, D. (1999). Commonwealth gender responsive budget initiative: Background papers. The Commonwealth Secretariat. Elson, D. (2000). Progress of the World’s women 2000. UNIFEM Biennial Report. United Nations Development Fund for Women. Elson, D. (2006). Budgeting for women’s rights: Monitoring government budgets for compliance with CEDAW . UNIFEM. Elson, D., & Cagatay, N. (2000). The social content of macropolicies. World Development, 28(7), 1347–1364. Grown, C., & Valodia, I. (Eds.). (2010). Taxation and gender equity: A comparative analysis of direct and indirect taxes in developing and developed countries. Routledge. Hurwicz, L. 1952. A criterion for decision making under uncertainty. Technical Report, 355. Cowles Commission. Kabeer, N., & Natali, L. (2013). Gender equality and economic growth: Is there a winwin? (IDS Working Paper No. 417). Institute of Development Studies. Klasen, S. (1999). Does gender inequality reduce growth and development? Evidence from cross-country regressions. World Bank Policy Research Report on Gender and Development. World Bank. Klasen, S. (2002). Low schooling for girls, slower growth for all? Crosscountry evidence on the effect of gender inequality in education on economic development. World Bank Economic Review, 16(3), 345–373.
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Kolovich, L. (Ed.). (2018). Fiscal policies and gender equality, IMF. Lahiri, A., Lekha, S. C., & Bhattacharya, P. N. (2002). Gender diagnosis and budgeting in India. National Institute of Public Finance and Policy. Maskin, E. (2008). Mechanism design: How to implement social goals. Les Prix Nobel 2007. 296–307. North, D. C. (1991). Institutions. Journal of Economic Perspectives, 5(1), 97– 112. Palmer. (1995). Public finance from a gender perspective. World Development, 23(11), 1981–1986. Polzer, T., Isabella, M. N., & Johann, S. (2021, September 13). A review of academic studies on gender budgeting, IMF Blog. Sayeh, A., Jiro, H., Carolina, R., & Vincent, T. (2021). Engendering the recovery: Budgeting with women in mind, IMF Blog, International Monetary Fund. Seguino, S. (2008). “Gender, distribution, and balance of payments constrained growth in developing countries.” PERI Working Paper 133. Political Economy Research Institute. Sen, G. (2000). Gender mainstreaming in finance ministries. World Development 28/7 . Sharp, R. (2003). Budgeting for equity: Gender budgeting initiatives within a framework of performance oriented budgeting. UNIFEM. Stiglitz, J., & Rasheed, H. (2020, June 8). Which economic stimulus works? Project Syndicate. Stotsky, J. G. (2016). Gender budgeting: Fiscal context and overview of current outcomes. (Working Paper 16/149). International Monetary Fund. Stotsky, J. G. (2021). Using fiscal policy and public financial management to promote gender equality. Routledge Studies in Gender and Economics. Roubini, N. (2022, February 25). Russia’s war and global economy. Project Syndicate. United Nations Development Programme (UNDP). (2010). Power, voice and rights: A turning point for gender equality in Asia and the Pacific. Macmillan World Bank. (2011). Gender equality and development. World Development Report. World Bank
CHAPTER 2
Macroeconomic Policy Coherence for Gender Equality in Asia-Pacific
Integrating gender budgeting in the rules-based policy space is challenging, especially when the macroeconomic policy framework itself is not flexible to integrate specific policy tools. Macroeconomic policy management is a significant element for delivering the Sustainable Development Goals (SDGs). It has been increasingly recognized as an important core strategy in the implementation of the SDG 2030 Agenda. Against this backdrop of COVID-19 pandemic, fiscal and monetary policy stimulus packages are designed by governments and central banks for economic growth recovery. The livelihood crisis is addressed through specific components in the fiscal stimulus packages including food security measures, strengthening social infrastructure, social protection, and the employment policies (Chakraborty et al., 2021). The liquidity infusion, maintaining status quo policy rates, and other regulatory measures are the major policy measures taken up by the central banks. The lack of proper fiscal and monetary policy coordination has also resulted in suboptimal policy outcomes (Chakraborty, 2021a, 2021b, 2021c, 2021d, 2021e; Chakraborty et al., 2021; Kaur et al., 2021; Stigliz & Rashid, 2020). The lockdown strategy without adequate emphasis to the principle of subsidiary through providing more powers to the lower tiers of government turned out to be partial in tackling the dual crisis of health and macroeconomic crisis. The fiscal space determined the size of the pandemic economic stimulus and given the constraints, the pandemic © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_2
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packages have not been enough to tackle the economic recession and livelihood crisis. This chapter analyses how macroeconomic policymaking—monetary, fiscal, and structural reforms—can be improved so as to contribute to the 2030 Agenda. Specifically, the chapter attempts to identify the significant constraints of the macro policymaking in the region and identify specific tools to understand how macro policies relate to the 2030 Agenda integrating the gender equality concerns. The SDGs were officially adopted by the member nations at the UN Summit in New York in September 2015. The SDGs are more ambitious than expiring MDGs as “leave no one behind” is the strategy adopted by the SDGs, by focusing on five key elements: people, planet, peace, prosperity, and partnership. There are 17 SDGs and 169 targets. Two global meetings need special mention in this context. One is the Addis Ababa Action Agenda on sustainable financing strategy and second the UN Climate Summit in Paris on a global agreement on climate change commitments. The SDGs hold the view that development needs to be economically, socially and environmentally sustainable. The commitment to the SDGs is made by each country at two levels: internal and external. The internal commitment aims to create enabling macroeconomic environment and robust sustainable growth. The external commitment is stability in trade and financial flows, and cooperation among countries to ensure a coherent macroeconomic policy framework. Specifically, the chapter focusses on the role of fiscal policy, to address the SDGs. The analysis carries out an overview of the focus of fiscal policy in Asia-Pacific and a normative assessment of what fiscal policy “ought to be” (normative) in achieving SDGs using a methodology to reach SDGs. It also analyses how structural and regulatory policies can contribute to achieving the SDG agenda. The role of monetary policy towards the implementation of the 2030 Agenda—incorporating the elements of prices, unemployment, and assets—is discussed and a critical analysis of monetary policy stance in the region is undertaken, conducive or not for SDGs. The empirical evidence suggests that economic growth does not translate into SDG attainment and therefore we need to identify the critical gaps and the complementary fiscal and monetary policies required to improve development outcomes.
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Fiscal Policy Stance SDGs require large public investments to achieve the goals by 2030. To ensure that, the countries require fiscal sustainability. However, a number of countries in the region have huge fiscal deficits, with fiscal consolidation measures on board. Fiscal consolidation is the rules-based policy initiative in the region where the fiscal deficit to GDP ratio is restricted to 3 per cent of GDP. Given the rule-based fiscal dynamics, which has led to the transition in the fiscal policy from discretion to rules, attaining SDGs would be a major challenge. Most countries, including China, Indonesia, the Republic of Korea, and the Russian Federation, had wider fiscal deficits or narrower surpluses and slower economic growth in the period 2014–2016 compared with the period 2011–2013, while India and Pakistan had higher economic growth and smaller fiscal deficits (UNESCAP, 2017). However, Chakraborty et al. (2021) revealed that many countries in the region have a high public debt-GDP ratio during the time of pandemic and a matter of concern if it is unaccompanied by high economic growth. As long as the real rate of interest (r) is below real rate of growth of economy (g ), it is plausible to run primary deficits. Indeed the use of public debt needs to be substantiated. If the high public debt is used for public infrastructure investment or for reducing the output gap, high public debt is desirable. In terms of debt sustainability, r > g is the point where debt becomes unsustainable and it can affect a country in meeting SDGs. In Sri Lanka, though debt-GDP ratio is above 100, r < g provides them leverage to engage in human development financing. In the South Asian region, Sri Lanka stands out in human development achievements irrespective of the fact that it is a low-income country. The impact of deficits on economic growth has been captured in two ways, one through the link between fiscal stance and output gap to arrive at whether fiscal policy is countercyclical (Tanzi, 2016), which is a shortrun fiscal consolidation exercise and the other link is through analysing the impact of the deficit on crucial macroeconomic variables including the rate of interest, private corporate investment (Chakraborty, 2016b). It is often debated that rule-based fiscal consolidation measures have provided Asia-Pacific region strong macroeconomic fundamentals. However, this argument is correct only if there is significant macroeconomic channels operating from fiscal deficit to other fundamental variables like rate of
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interest, private investment, rate of inflation and capital flows. Empirical evidence is mixed, if deficit causes rise in real interest rates and there are strong fiscal-monetary linkages in the region (Chakraborty, 2016a, 2016b). The real interest rates are mostly determined significantly by inflationary expectations, not deficits. This is especially true in the context when Central Banks in the region increasingly moving towards rule-based inflation targeting framework. Financial crowding out through pre-emption of resources for financing deficits and in turn restricts the loanable funds available to private sector. However, empirical evidence revealed that public investment crowds-in private corporate investment (Vinod et al., 2020). If the impact of deficit is increasingly nil in worsening the macroeconomic fundamentals, the argument that fiscal prudence through deficit control mechanisms is essential for sustainable growth in the region fails. This may be confirmed looking into the patterns of fiscal policy stance in the region, especially during negative shocks like the global financial crisis of 2007/08. It is the fiscal re-dominance that helped the region to cope with the global financial crisis through economic stimulus packages than the fiscal prudence of restrictive public spending. Enhancing the role of fiscal policy stance for inclusive policies for SDGs may or may not have trade-offs with fiscal sustainability. Over the years, the fiscal policy stance in Asia-Pacific is to sustain economic growth through public infrastructure investment and human capital formation. This leads to the question what “ought to be” the role of the State in the region to maintain and achieve the SDGs—a “security state” or a “development state” (Horst et al., 2017). In the context of G20 countries, it has been revealed that public spending on innovation and human capital formation has more impact on economic growth (Horst et al., 2017). Other studies have concluded that public spending on defence does not ensure peace, security and stability (SIPRI, 2017). Public spending in Asia-Pacific is lower than in advanced economies. This makes it compelling to analyse whether strict adherence to fiscal rules is for fiscal prudence in revenue/current expenditure or has it eroded the capital formation in the region which in turn has severe long-term growth consequences. If fiscal prudence is achieved through less or no spending on capital formation, the fiscal consolidation may result in stagnation in economic growth. The path of fiscal consolidation may be as important as the target of fiscal consolidation. If the targets are achieved through cuts
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in capital spending, fiscal responsibility legislation to control the deficit might lead to adverse macroeconomic consequences. Phasing out revenue deficit (revenue deficit is revenue expenditure minus revenue receipts. It is also referred to as current deficit in fiscal literature) is yet another significant tool of fiscal consolidation. Early warning signals need to be provided to the Asia-Pacific region to design their fiscal consolidation packages judiciously. These policy articulations have direct consequences for achieving SDGs. Fiscal stance and output gap links need to be empirically analysed to understand whether the fiscal policy is countercyclical or pro-cyclical (Chakraborty & Chakraborty, 2006; Chakraborty & Kaur, 2020). Restrictive macroeconomic policies might result in constrained fiscal space to sustainably finance the implementation of the SDGs. Empirical analysis showed that expansion in fiscal space is more likely to be sustainable when public spending finances investment rather than consumption (Roy & Heuty, 2009). Economic growth and debt sustainability are the two significant priorities of the fiscal policy regime in Asia-Pacific. If the region has to frame the fiscal policy for SDGs, the policies may have to move forward from economic growth paradigms and fiscal rule-based policy prescriptions. Asia-Pacific countries need sustained economic growth to reach advanced economies, but if growth is at the cost of inclusiveness, SDGs cannot be met because the majority of people in the region live in poverty. It is also relevant to analyse the structural transformation, along with the aggregate economic growth. What kind of structural transformation that promotes economic growth and employment is an empirical question, specific to country-contexts. Decent jobs are a matter of urgent concern, especially when informal employment accounts for about 70 per cent of all jobs in Sri Lanka, almost 90 per cent in Bangladesh, India, and Pakistan, and up to 95 per cent in Nepal (ILO, 2015). There is also a significant empirical link between governance and the ability of the countries to raise tax revenue. The reasons may be corruption in tax collection and low tax morale due to perceived governance deficits. Considering the relationship between governance and social development, it has been shown that the efficiency of the public provisioning of health and education services is affected by governance performance, particularly through corruption and ineffective bureaucracy (ESCAP). Governance is a crucial determinant in reducing the income
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and development gap in Cambodia, Lao People’s Democratic Republic, Myanmar, and Vietnam (CLMV) countries, along with other factors such as the availability and quality of physical capital, the availability of decent, skilled and productive jobs, strong macroeconomic fundamentals, wage and social protection systems, or effectiveness of the fiscal policy. From the SDGs perspective, it has been found that ineffective governance and weak institutions can exacerbate income inequality. On fiscal policy, the issues are related to what rules governments should follow, e.g. should they have a maximum level of fiscal deficit, debtto-GDP or tax-to-GDP? The consensus among the macro policymakers was that there is no golden rule. For instance, to analyse fiscal deficit issues, besides quantity, governments should also consider quality. There was no consensus on which “deficit” needed to be targeted to remain fiscally prudent—whether revenue deficit, primary deficit (fiscal deficit minus interest payments), or fiscal deficit. As the revenue generation of various nations is predominantly hydroelectric power generation among the LDCs in the region, it may also be worth exploring the Public Sector Borrowing Requirement (PSBR) to measure the deficits as it includes the intra-public sector budgetary transactions in addition to the governmental budgetary transactions. In terms of fiscal policy, policy deliberations among countries were about using progressive taxation systems and having social security and safety nets—under several formats. Inequality, as measured by the Gini coefficient, is often a problem. Some countries such as Bhutan have education and healthfully subsidized, which is particularly good because it favours inclusiveness. In Bangladesh, the financing required to achieve the SDGs was estimated at 1 trillion USD. Then it was studied how much could be contributed by the different stakeholders. Once the financing gap was identified, tapping capital markets and local currency bonds is expected. The country’s strategy is to create an enabling environment where finance can be mobilized, both in local and international currency, both by national and foreign actors. The Universal Basic Income (UBI) may be another option. However, as the capacity of health and education infrastructure is poor in many countries in the region, the UBI may not be enough to achieve the intended results.
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Effective Fiscal Management and Governance A global governance arrangement and regulatory framework is required to make sure that foreign investment promotes equality and sustainability as well as economic growth across geopolitical entities. A global governance arrangement and regulatory framework is required to make sure that foreign investment promotes equality and sustainability as well as economic growth across geopolitical entities. A transparent and equitable tax system is a prerequisite for adequate revenue mobilization to meet SDGs. The Panama Papers released in April 2016 revealed 214,488 offshore tax havens, created through tax avoidance. Reforms are required to track illicit financial flows and flaws in the global financial architecture. The introduction of GST in India is expected to bring transparency into the system as tax invoices are required to redeem tax credit and this in turn is expected to prevent tax avoidance, and avoid cascading effects of multiple taxation at various levels of inputs. There is a growing recognition towards domestic resource mobilization and fiscal self-reliance to achieve SDGs. Fiscal consolidation through enhanced tax buoyancy is better than cuts in expenditure. A few countries have introduced innovative taxes, for instance, carbon tax, which could be an additional source of financing SDGs. Inequalities in Fiscal Policy Monitoring outcomes of public expenditure is equally significant as designing public expenditure policies. The public expenditure benefit incidence analysis (BIA) across categories of gender, geography, and social groups can capture the distributional impacts of public spending. The public expenditure BIA is based on two factors: unit costs and unit utilized. The unit costs are prepared from budgets, while unit utilized data is collected from sectoral National Sample Surveys. The BIA quintile wise revealed that in India and in the Philippines, the poor (q1) depend on public provisioning of health care and education. It can be technically analysed using concentration curves of BIA, whether the public spending on education and/or health care is pro-poor. The public spending BIA deciphered that the access and utilization of public spending are regressive in the Philippines and India, with gender-differentiated patterns while in Sri Lanka a study showed gender parity in the utilization of public provisioning across sectors. These empirical evidences showed that unless
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governance and implementation issues are taken care of, a well-designed public spending system can be regressive—and therefore continue making it difficult to attain the SDGs. Inequalities in fiscal policy incidence can be captured through BIA. We will revisit this in Chapter 10. Higher budgetary allocation per se does not ensure higher spending. There can be budget forecast errors or unspent money which in turn affects the outcomes. Capturing this deviation or errors between budget estimates and actual spending is called “fiscal marksmanship analysis”. The analysis can determine whether these deviations or errors are random or happened due to some policymaking bias. Fiscal marksmanship is the accuracy of budgetary forecasting. This can be one important piece of such information the rational agents must consider in forming expectations. Empirical studies have used Theil’s inequality coefficient (U) based on mean square prediction error, to estimate the magnitude and sources of budgetary forecast errors. In the context of India, the analysis revealed that neither revenue nor expenditure forecasts uphold rational expectations (Chakraborty & Sinha, 2018). It was also revealed that the capital budget revealed more forecast errors than the revenue budget (Chakraborty & Sinha, 2018; Chakraborty et al., 2020c; Nitin & Roy, 2016). If the proportion of error due to random variation is significantly higher, it reflects that these errors have beyond the control of the forecaster or the macro policymaker. In India, empirical studies showed that errors due to policymaker’s bias have been negligible. Fiscal marksmanship is conducted at the aggregate revenue and expenditure categories. From the SDGs perspective, sectoral fiscal marksmanship analysis is highly relevant, and therefore a matter for future macroeconomic policy research in the region. Linking Resources to Results: Outcome Budgets Several countries in the region have undertaken fiscal reforms to promote efficient fiscal management and fiscal sustainability. These initiatives include Fiscal Councils, Medium Term Fiscal Framework (MTFF), accrual accounting, and outcome budgets. Fiscal Councils are autonomous public institutions aimed at strengthening commitments to sustainable public finances through various functions, including public assessments of fiscal plans and performance, and the evaluation or provision of macroeconomic and budgetary forecasts. Medium-term Expenditure Framework Statement is a statement presented to the Parliament, which outlines a
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three-year rolling target for the expenditure indicators with the specification of underlying assumptions and risks involved. Accrual accounting is an accounting method that measures performance regardless of when cash transactions occur. Outcome budgets aim to measure and control the expenses of concerned ministries to introduce effectiveness in the public expenditure. These fiscal reforms aim to improve the performance, efficiency and prioritization of public spending by converging national and line ministry’s outcomes with programmes and budgetary resources through integrating planning, budgeting, and auditing. SDGs are integrated in this processes or not in these countries is a matter of concern. There is a growing recognition that fiscal policy can affect household dynamics, for instance, division of labour by supporting initiatives that reduce the burden of women in unpaid care work. Examples of such government intervention are improved infrastructure in the water sector, rural electrification, sanitation services, and better transport infrastructure. The public infrastructure deficit in rural areas may deepen rural poverty due to the time allocation across gender skewed towards more unpaid work, which is time otherwise available for income earning market economy activities. Public investment in infrastructure, like water and fuel, can also have positive social externalities in terms of educating the girl child and improving the health and nutritional aspects of the household (Chakraborty, 2008). There can be a link between deterioration in infrastructure and rural poverty. Raghabendra and Duflo (2001) analysed whether feminization of governance alters public expenditure decisions favouring women’s preferences and needs. They measured the impact of the feminization of governance at the local level on the outcomes of decentralization with data collected from a survey of all investments in local public goods made by the village councils in one district in West Bengal. They found that women leaders of village councils invest more in infrastructure that is relevant to the needs of rural women (like drinking water, fuel, and roads) and that village women are more likely to participate in the policymaking process if the leader of their village council is a woman (Chakraborty, 2010). Stern (2002) highlighted their inferences that placing women in local level governance can change the expenditure decisions of the local bodies and, in turn, change the types of public-good investments at the local level to correspond more to the revealed preferences (voice) by women.
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In terms of fiscal policies to redress poverty, the aspects of time poverty are often surpassed. An individual is time poor if he/she is working long hours and is also monetary poor, or would fall into monetary poverty if he/she were to reduce his/her working hours below a given time poverty line. Time poverty affects income poverty. Fiscal policies designed to redress income poverty can be partial if they do not take into account the aspects of time poverty. This policy discussion has a gender dimension, as women are time poor, and fiscal policies designed for pro-poor measures need to incorporate the time allocation aspects across gender (Chakraborty, 2014a, 2014b, 2016a; Chakraborty et al., 2020a). Using time use statistics of water revealed that the incidence is significantly higher for girls and women in both rural and urban areas, which, in turn, points to the deficiency in adequate infrastructure in water and sanitation (Chakraborty, 2008). It has significant fiscal policy implications, as easy accessibility to drinking water facilities might lead to an increase in school enrolment, particularly for girls, by reducing the time utilized for fetching water. The time budget statistics enable the identification of the complementary fiscal services required for better gender-sensitive human development. In fiscal federalism, SDG commitments cannot be confined just to the national governments. There is a growing recognition of the role of intergovernmental fiscal transfers (IGFT) in SDGs to integrate climate change and disaster management. However, there are relatively a few attempts to translate the financial devolution commitments into SDG commitments. This financial devolution refers to intra-country arrangements, not intercountry arrangements. This fiscal devolution refers to the flow of funds from the upper government to lower tiers of government, which is also referred to as Inter-governmental fiscal transfers (IGFT). For instance, the Fourteenth and Fifteenth Finance Commissions in India have incorporated climate change variable as one of the criteria for devolution of funds. This is a radical approach because the criteria of devolution across countries in the region are more or less confined to fiscal and growth variables. Variables relating to natural disasters also form part of fiscal devolution, as an exogenous shock at the subnational government levels, and usually, the disaster management devolution is granted through specific transfers than through unconditional formula-linked fiscal transfers. This opens a significant debate of integrating human development-related variables in fiscal devolution. As another example, Chakraborty (2010) has argued for integrating gender criteria in IGFT.
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Normative Framework and Methodology to Analyse the Fiscal Policy for Gender Equality Sen’s Capability Approach may provide an analytical framework to build a normative framework and methodology to analyse the fiscal policy for SDGs. Such frameworks were used by Meghnad Desai in his Discussion paper at the London School of Economics, in integrating poverty and inequality variables in “ought to be” macro policies using Sen’s framework and methodology. It is plausible to adopt this normative framework to integrate SDGs into the macro policy framework (Chakraborty, 2020). In terms of Sen’s capability approach, there are three crucial layers, which need interpretation in the context of SDGs: capabilities, functioning, and commodities. Capability Approach has been central to the Human Development Reports series (HDRs) launched by UNDP in 1990s by Sen’s close associate, the late Mahbub ul Haq, and has subsequently influenced policy at World Bank during the Wolfensohn era (Gasper, 2002). It provided a channel for an alternative economic development thinking, which goes beyond the undue emphasis on economic growth as in the economic planning of the 1970s and its trickling-down effects. It revealed that GDP (economic growth) was never suited to be a measure of well-being as it conceals extreme deprivation for large parts of the population. The first step of the capability approach is to propose a list of basic capabilities relates to 17 SDGs. Basic capabilities can be a set of capabilities that should have only a few elements and this set is common for all individuals. These capabilities can be the capability to stay alive and live long, the capability to lead a healthy life, the capability to have the knowledge, the capability to have social interaction, etc., which are closely linked to SDGs. The second step would be to gather relevant information on the functioning of different socio-economic variables, that are observable data. In this step of listing the functionings, the data needs to be incorporated in terms of SDG targets. The third step is to estimate the optimal commodity space, especially the fiscal and monetary policy stance in terms of SDGs, which is necessary to be at the individual’s command to match commodity characteristics and capability requirements and then analyse the actual commodity space to identify the gaps.
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Monetary Policy Stance Globally there is a growing recognition about how to address the challenges of existing macroeconomic thinking and policymaking—both fiscal and monetary policies—including the issues related to inflation, unemployment, rising inequality, stagnating productivity, and unresponsiveness of long-term interest rates to rising public debt, among others (Chakraborty et al., 2021). Blanchard and Summers (2017) highlighted the use of monetary and fiscal policy tools to reduce risks and react to adverse shocks through stabilization measures. They have also argued for active financial regulation and macro-prudential policy measures to reduce inequalities. Bernanke (2017) in a paper titled “Monetary policy in a new era” has highlighted that Central Bankers are looking forward to an era of relative financial and economic stability in which growth and distribution—growth and inequality—the issues that are the “not primarily” the province of Central bankers, but how monetary policy can meet these challenges of growth and rising inequalities. Furman (2017) in his paper titled “Should policymakers care whether inequality is helpful or harmful for growth?” argued that high levels of inequality can make sustained growth impossible or even cause recessions. He argued that exogenously higher levels of inequality result in lower longer-run growth rates and policy coordination is required to address this. This has direct policy inferences for integrating SDGs in macroeconomic policies to reduce widening inequalities. Furman (2017) further argued that equal weight to $1 added to the income of a poor person or a billionaire is misplaced, and most social welfare functions would place more weight on the bottom than on the top. Therefore, the macroeconomic policies—monetary and fiscal policies—that reduce inequality while increasing growth are clearly worth prioritizing. Against this backdrop, the calibration of regulatory frameworks, both discretion and rules in the financial system, requires reforms. The monetary and financial system are dynamic and adaptive to address the question of inequalities. The distributional effects of many policies are orders of magnitudes larger than the growth effects (Furman, 2017). This section would be focusing on different targets (prices, unemployment, assets) that the Asia-Pacific region has been applying in the monetary policy stance and collating the evidence of these developments in the Central Bank’s perspectives of monetary policy targets in the region.
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The role of monetary policy is primarily price stability, credit control, financial inclusion, and debt management. In other words, the objectives of central banks are maintenance of price and exchange rate stability and curbing inflationary pressures. The emerging market economies in Asia have increasingly adopted monetary policy strategies to establish price stability, especially after the global financial crisis (Filardo & Genberg, 2010). The countries have adopted inflation targeting approaches to peg their policy rates based on the nominal anchor. Inflation targeting has been accepted by advanced countries as the superior framework of monetary policy (Bernanke et al., 1999). Most countries follow a specific monetary policy regime, to provide an institutional structure for the monetary policy stance. This regime also decides on the tools of the monetary policy and the decisions to be communicated clearly to the people. The basic monetary regimes include monetary targeting, exchange rate targeting, a regime with inflation targeting, and a regime with an “implicit” nominal anchor. A multiple indicator approach is also followed by many Central Banks. In the monetary targeting regime, the monetary aggregates are targeted. The growth of chosen monetary aggregate—money supply—is closely watched in this regime. This is based on the assumption that in the long term, the rate of change in prices (inflation) is affected by the money supply. The choice of selecting a desirable monetary aggregate is with the specific country. However, over the years, Central Banks have realized that digitization, financial innovation, and financial liberalization have weakened the relationship between monetary aggregates and price changes. The Central Bank announces an inflation “target” under the inflation targeting regime, and frames policy relates to achieving this target. Inflationary expectations form a crucial determinant of this regime. In many countries, expectations surveys are carried out to arrive at inflationary expectations. This regime requires wider information than just information on monetary aggregates and exchange rates. This regime requires information about employment, labour markets, the output gap (the deviation of actual output from the potential output), nominal and real interest rates, fiscal variables, and the nominal and real exchange rates. Each country articulates their policy rates, inflationary expectations and the “target” of inflation differently. Exchange rate targeting focusses on nominal exchange rate stability pegging to a currency of an “anchor” country through FOREX interventions or interest rate differentials. This regime thus “imports” price
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stability from the anchor country. The exchange regime requires a sufficient level of international reserves and a macroeconomic policy which ensures minimum inflation differentials between the country and the anchor country, and a favourable Terms of Trade and competitiveness and political stability. The legal and institutional framework is important for the exchange rate regime to function without uncertainties. The autonomy of monetary policy is constrained to a great extent under the exchange rate regime. A regime with an implicit nominal anchor is targeting a variable without it being announced explicitly by the Central Bank. The credibility of Central Bank is highly significant for arriving at “implicit” nominal anchor, internally by the monetary policymakers. The Central bank internally makes the desirable changes in inflationary expectations to achieve the price stability, without announcing it publically, using explicit targets. Apart from inflation targeting regime, monetary policy has several other regimes as mentioned above. In most of the Asian countries, an eclectic policy regime is also framed in case of monetary policy. Inflation targeting, is usually misunderstood as just targeting the rate of inflation as an objective of economic policy. In reality, inflation targeting includes five steps. One, the setting a numerical target range for the rate of (price) inflation, usually Central Bank in coordination with the Government. Two, the use of monetary policy as the key policy instrument to achieve the target, with monetary policy pegging the policy rate incorporating inflation expectations. Three, the operation of monetary policy is in the hands of an “independent” Central Bank, unless an agreement between Central Bank and the Government is framed for a Monetary Policy Framework. Four, the monetary policy is only concerned with price stability. Usually, the other plausible effects of monetary policy on other policy objectives including economic growth are ignored. Chakraborty (2021e) narrates the policy uncertainty about interest rates—against the backdrop of a plausible decision by US Fed to raise the interest rates— whether to maintain the status quo to protect growth recovery or to raise the rates to pre-empt a capital flight. Yet another significant issue is to distinguish between goal independence and operational independence. What independence do central banks seek? In India, Monetary Policy Committee (MPC) was set up in 2016 for operational independence. In the Report of Currency and Finance published by the Reserve Bank of India in 2021, empirical evidence was provided in favour of a new monetary policy framework
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in providing price stability (RBI, 2021). It is often argued that it is more relevant for the government to set a goal of price stability and pursue the central bank towards this goal by independently setting the operations and instruments. The instrument independence enables the central bank to be forward-looking. Yet another limitation of undertaking monetary policy within committees is that committees can tend to be inertial and maintain the status quo in maintaining policy rates in the monetary policy stance for long. The MPCs may laboriously aggregate individual preferences that tend to be inertial, irrespective of whether is a strong Chairman for MPC or not. This would in turn lead the central banks to overstay their stance. Inflation targeting may not be a sufficient tool to handle balance sheet problems. These imbalances in the balance sheets may not have immediate impacts on inflation, but they have impacts on output and employment. The ultimate form of these balance sheets disorder can be asset price bubbles, which inflation targeting may not address effectively. Against the backdrop of COVID-19 pandemic, central banks have engaged in emergency bond purchase programmes to provide liquidity (Chakraborty et al., 2021). Flexible inflation targeting is a long-run monetary policy strategy to minimize price instabilities as well as minimize the fluctuations in the output (unemployment). Because the main limitation of “nominal anchor” is that such an inflation target does not leave much room for macroeconomic stabilization in terms of output fluctuations as it is confined only to price stability. The flexible inflation targeting framework provides simultaneously space to a dual mandate to monetary policy—both price stability and macroeconomic activity—to focus on both output (unemployment) and price fluctuations. The flexible inflation targeting accommodates symmetrically both inflation and the output gap. This central bank’s function contains forecasts for both inflation and output gap as target variables. However empirical evidence from the region are mixed regarding the impact of monetary policy on economic growth.
Structural Reforms This section deals with how can structural reforms contribute to achieving the SDG agenda. Structural policies are defined as the macroeconomic policies framed to impact the total factor productivity (TFP) of the country, incorporating the regulatory policies. Total factor productivity
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can be obtained as the residual from sector-specific estimations of a logarithmic Cobb–Douglas production function, and the coefficients can be estimated using Levinsohn and Petrin (2003). Taking natural logs of Cobb–Douglas production function in a linear function, we obtain where is the physical output of firm i in period t; Kit , Lit , and Mit are inputs of capital, labor, and materials, respectively; and Ait is the Hicksian neutral efficiency level of firm i in period t and where β 0 measures the mean efficiency level across firms and over time; εit is the time- and producerspecific deviation from that mean, which can then be further decomposed into an observable and unobservable component. These structural policies comprise innovation policies, price and energy policies, regulations and labour market policies. Looking into the determinants of TFP, the following variables have been denoted: knowledge and skills; education and research and development activities; exports, imports and FDI and institutional quality, good governance and infrastructure. It has been suggested that Asia-Pacific economies made progress in enhancing the quality of labour forces, with the increase in the average years of schooling of adults, the literacy rate, and the net enrolment rate at the secondary level. Average public spending on research and development activities in the region has increased in terms of GDP, to almost equal to the world average—though slightly below the OECD average. The expansion of trade that has taken place in the Asia-Pacific region over the past 25 years, and the dramatic increase in FDI into the region have contributed to the overall increase in total factor productivity. Poor governance, low institutional quality and inadequate infrastructure can negatively affect TFP growth by increasing the cost of inputs. Countries with lower levels of corruption experience higher TFP growth. Lack of physical infrastructure, in particular, transport infrastructure and trade facilitation systems increases costs of production and reduces TFP. The structural policies by government for lifeline infrastructure like electricity, gas, mining and communication services are significant for enhancing economic growth. In India, the recent policy reform to absorb the power debt of the DISCOMS (electricity distribution companies) is called UDAY (Ujjwal Discom Reassurance Yojana). UDAY is introduced in a special context where the country has excess power generation, but due to the huge debt of DISCOMs the power is not distributed across Provinces and many poor live without electricity. This policy was introduced to provide electricity to the poor by correcting the financial and operational efficiency parameters of DISCOMs (Kaur & Chakraborty, 2019; Kaur et al., 2021). The procedure consisted of the state governments absorbing the power debt of DISCOMs—by issuing
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bonds through a tripartite form between the Central government, State government, and the DISCOMs. Though the programme has led to marginal improvements in access for poor to electricity, the subnational public finance of a few States has encountered problems in terms of their deficit going up beyond the fiscal legislations, which hindered these states not to accessing excess borrowing powers in the bond market which otherwise they were entitled to. From the SDG perspective, though this programme is to provide “lifeline infrastructure”, it has aggravated the public finance management issues by exploding the debt deficit conundrum in particular states. Another major structural policy initiative in the region is related to natural resources and extractive industries. Despite having one of the highest reserves of coal, India is also the highest importer of coal. The carbon tax is framed from the production and import of coal, with 500 Rupees per metric ton, to be used as clean energy access (Chakraborty, 2014c; Chakraborty et al., 2016, 2020b). Yet another major initiative is to link the fiscal space derived from mining revenue to the spatial and human development of the region where the revenue is extracted from. These social impact policies relating to extractive industries are rare. As per the recent MMDR policy a fund is created as DMF to link fiscal space to human development. This has positive implications in terms of SDG, as the socio-economic indicators of the mining districts are the worst in the country when compared to non-mining districts. Such policies can be compared to BEE (Black Economic Empowerment) policy of South Africa and Oil-to-Cash policies of Ghana, linking fiscal space to human development in the mining sector. The financial sector legislation reforms commission (FSLRC) in India has prepared the Indian Financial Code, which is another highlight of the structural policy initiative. The aim of FSLRC is to ensure a sound financial system with less Ponzi finance and in turn, lead to higher economic growth. The labour market reforms are relevant especially when growth is not followed by an increase in jobs. The states like Rajasthan and Maharashtra have begun to loosen rules for hiring of labour. The labour market policies should attempt to avoid both excessive regulation and extreme disregard for labour conditions. Improving skills and Start Ups are other initiatives to improve productivity. The bankruptcy code introduced in India is a structural reform to give a public resolution and restructuring for the firms in loss and for a turnaround.
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Mapping of Macro Policies in Asia-Pacific This section maps macro policies on SDGs in the region and provides examples. However, this mapping is not comprehensive with all 17 SDGs. Widening inequalities within and between countries in wealth, opportunity, and power as well as persistent gender inequalities are confronting the world today and hence formed the framework for the 2030 Agenda for Sustainable Development. The United Nations System Shared Framework for Action 2017 has articulated the need to build upon the lessons of the Millennium Development Goals (MDGs), and move towards the commitments to “leave no one behind” and to reach the furthest behind first. It aims not only to end poverty and hunger, but also “to combat inequalities within and among countries; to build peaceful, just and inclusive societies; [and] to protect human rights and promote gender equality and the empowerment of women and girls” and “to ensure that all human beings can fulfil their potential in dignity and equality and in a healthy environment”. At the national level, governments must attempt to boost investor confidence, strengthening public finances, social inclusion, and environmental regeneration. A global analysis of normative SDG assessments of SDG14 is carried out by IIED showed how fiscal instruments can be designed to provide the necessary incentives for achieving SDG 14 and the goal of leaving no one behind, using of three particular fiscal instruments (taxes, subsidies and conditional transfers) to this sector. Empirical studies have analysed the fiscal policy tools in green economy sector linking to SDG and how to integrate climate change commitments within public policy frameworks (Andersen & Ekins, 2009; Chakraborty, 2021c, 2021d; Heine et al., 2012; Kaur & Chakraborty, 2019). Examples are rare in the region in terms of technical cooperation for SDGs. UNESCAP highlighted one such recent initiative- “Evolution” initiative—launched by Japan to provide developing countries with a one-stop mechanism including technical support, for preparing energy policies. Other examples are the Green Technology Center-Korea (which links the Republic of Korea’s public–private cooperative green technology research projects with the demand for green technology from developing countries) and a new centre jointly planned by China’s National Energy Administration and the International Energy Agency to enhance partnership in attaining energy data, renewable and clean energy policy technologies.
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The fiscal policy in health sector of Pacific Islands analysed by UNESCAP revealed that highly constrained national budgets of Pacific island developing economies are often subject to volatility from a narrow revenue base, dependency on foreign aid and recurring external shocks, such as natural disasters. The Pacific Islands require a better design and implementation of fiscal policy to improve health outcomes while ensuring fiscal sustainability. Public spending on health in most Pacific island developing economies averaged close to 9 per cent in 2014, ranged between almost 5 per cent of GDP in Fiji and Papua New Guinea to about 17 per cent of GDP in Marshall Islands and Tuvalu. This is higher than the case of India where public spending on health by national governments is only around one per cent of GDP.
Identifying Specific Policy Tools The role of fiscal policy in attaining SDGs may take two routes. One, a route of fiscal policy, acting as “employer of last resort” by providing “participation income” in return to economic activity. Two, fiscal policy acting as a provider of “basic income” to all citizens unconditional and non-targeted. In Asia-Pacific, fiscal policy has acted the role of providing “participation income” through employment programmes rather than “basic income”. Globally, “participation income” is attained through a direct employment transfer—a Job Guarantee programme—which is an “employer of last resort” fiscal policy. This policy envisions the government bearing a guarantee to provide paid work opportunities of predictable duration at a predetermined wage for public works. Though many such job guarantee initiatives have been introduced over the years across the countries, the popular and largest in scale are the US New Deal programmes, ex post to 1929 Great Depression; the Jefes programme in Argentina and the Expanded Public Works Programme (EPWP 2004– 2005) in South Africa, other than the Mahatma Gandhi National Rural Employment Guarantee Act in India, specific to the region. These programmes are targeted at labour-intensive work in the field of environmental interventions and in providing public benefits in asset-creating public works. A major lacuna of the existing studies on job guarantee programmes is the lack of analysis on the impact of time use patterns and in turn the care economy infrastructure in strengthening the participation of women in wage employment. It is based on the principle of self-selection, and
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it is a step towards legal enforcement of the right to work, as an aspect of the fundamental right to live with dignity. This programme aims to redress the seasonal, cyclical, and structural unemployment in the country by providing the low-skilled poor a work entitlement thereby ensuring that when all else fails, the government acts as “employer of last resort”. On the other hand, “basic income” is an unconditional cash transfer. It can be universal or targeted, and can involve 2 types of errors: I or II. It is often argued that universal is better than targeted as the latter can encounter exclusion I error (non-targeted getting included) and exclusion II error (needy getting excluded). The fiscal implications of universal basic income is a matter of concern within the constraints of fiscal rules. It is always a dilemma for the government to design “universal basic” income or “participatory” income. If the priority of the government is to design policies to enable people to “participate” in economic activity, then they go for employment-related policies. However, “basic income” has received significance amidst the increasing automation process and lack of job availability. In addition to these two fiscal policy designs, energy subsidies also form a major policy. The fossil fuel subsidy is increasingly phased out or better targeted in the region. In India, the policy to provide clean fuel at affordable prices to the poor is considered a major public policy in terms of gender equity. As women spend disproportionate hours collecting fuel wood and spend prolonged hours cooking with non-clean fuel with poor ventilation can lead to increase in health risks of respiratory diseases. UNESCAP (2017) pointed out that in Asia energy subsidies (especially on petroleum products and electricity) accounted for about one third of global energy subsidies in 2013. Such subsidies accounted for about 20 per cent of GDP in the Islamic Republic of Iran, followed by the Russian Federation and India (both at about 10 per cent), Indonesia (7 per cent) and China (4 per cent). In the wake of the global oil price decline in 2014, a number of countries, including Indonesia, have aggressively phased out fuel subsidies. Financial inclusion means that individuals and businesses have access to useful and affordable financial products and services that meet their needs—transactions, payments, savings, credit, and insurance—delivered in a responsible and sustainable way. In India, the first-ever unique identification project, where identities are biometrically scanned, is enabling unbanked individuals to access credit and other banking services through JanDan project. In the Asia-Pacific region, the Philippines has enabling
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policy environment and business support which helped in implementing affordable and efficient financial services (micro savings and micro insurance) to the poor through technological innovations and mobile banking. In July 2017, the Asian Development Bank (ADB) and Cantilan Bank, in partnership with Oradian, launched a pilot project on cloud-based core banking technology in the southern Philippines to provide digital financial services to poor in hard to reach terrains in Philippines. This digital financial services provide platform for the poor people to save, make a payment, get a small business loan, send a remittance, or buy insurance. TabunganKU (My Savings) and People’s Business Credit are the two significant microfinance programmes in Indonesia. The private sector also plays an active role in Indonesia in microfinance programmes. For instance, Bank Rakyat Indonesia, a private bank, has introduced financial inclusion projects to serve unbanked firms and individuals. In Thailand, financial inclusion is prominently pursued by the Government. The Village Fund of Thailand is recognized as one of the largest microfinance institutions in the world, providing subsidized credit to farm households and small firms in rural areas. To conclude, the inventory analysis of macro policies for SDGs reveals that the countries in the Asia-Pacific region do not have any policy documents relating to macroeconomic policies to attain the SDGs. Broadly, policymakers have articulated a plethora of legislative and regulatory mechanisms to implement SDGs at national and subnational levels. However, the most significant, and often overlooked, are the macro policy tools that they have to complement these broad approaches.
References Andersen, M. S., & Ekins, P. (Eds.). (2009). Carbon-energy taxation: Lessons from Europe. Oxford University Press. Blanchard, O., & Summers, L. (2017). Rethinking stabilization policy. Back to the future (Working Paper). Peterson Institute for International Economics. Bernanke, B. (2017). Monetary policy in a new era (Working Paper). Copublished by Peterson Institute for International Economics and Hutchins Center on Fiscal and Monetary Policy. Bernanke, B. S., Laubach, T., Mishkin, F. S., & Posen, A. (1999). Inflation targeting: Lessons from the international experience. Princeton University Press. Chakraborty, L. (2008). Deficient public infrastructure and private costs: Evidence from a time-use survey for the water sector in India (Working Paper No. 536). Levy Economics Institute.
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Chakraborty, L. (2010). Determining gender equity in fiscal federalism: Analytical issues and empirical evidence from India (Working Paper No. 590). Levy Economics Institute. Chakraborty, L. (2014a). Gender budgeting, as fiscal innovation (Working Paper 797). The Levy Economics Institute. Chakraborty, L. (2014b). Integrating time in public policy: Empirical description of gender-specific outcomes and budgeting (Working Paper 785). Levy Economics Institute. Chakraborty, L. (2014c). Revival of mining sector in India: Analysing legislations and royalty regime (Working Paper No. 129). National Institute of Public Finance and Policy. Chakraborty, L. (2016a). Asia: A survey of gender budgeting experiences (Working Paper 16/150). International Monetary Fund. Chakraborty, L. (2016b). Fiscal consolidation, budget deficits and macroeconomy: Monetary-fiscal linkages. Sage Publications. Chakraborty, L. (2020). Macroeconomic policy coherence for SDG 2030: Evidence from Asia Pacific (Working Paper 292). National Institute of Public Finance and Policy. Chakraborty, L. (2021a). Union Budget 2021a–22: The macroeconomic framework. Economic and Political Weekly, 56(9). Chakraborty, L. (2021b). Fiscal federalism, expenditure assignments and gender equality (Working Paper 334). National Institute of Public Finance and Policy. Chakraborty, L. (2021c). Mainstreaming climate change commitments through finance commission’s recommendations. Economic and Political Weekly, 56(33). Chakraborty, L. (2021d, October 22). Greening the monetary policy. Editorial Column. The Financial Express. Chakraborty, L. (2021e, October 14). Why RBI has not been hawkish in its monetary policy? The Indian Express. Chakraborty, P., & Chakraborty, L. (2006). Fiscal stance and output gap: An empirical estimation, The Policy Innovations, Carnegie Foundation. Chakraborty, L., & Kaur, A. (2020, December 23). Why output gap is controversial? The Financial Express. Chakraborty, L. S., & Sinha, D. (2018). Has fiscal rule changed the fiscal marksmanship of union government? Anatomy of budgetary forecast errors in India (Working Paper 234). National Institute of Public Finance and Policy. Chakraborty, L., Garg, S., & Singh, G. (2016). Cashing in on mining: The political economy of mining regulations and fiscal policy practices in India (Working Paper 161). National Institute of Public Finance and Policy. Chakraborty, L., Nayyar, V., & Jain, K. (2020a). The political economy of gender budgeting: Empirical evidence from India (Working Paper No. 256). National Institute of Public Finance and Policy.
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Chakraborty, L. S., Thomas, E., & Gandhi, P. (2020b). Natural resources revenue buoyancy in India: Empirical evidence from state-specific mining regime (Working Paper No. 313). National Institute of Public Finance and Policy. Chakraborty, L. S., Chakraborty, P., & Shrestha, R. (2020c). Budget credibility of subnational governments: Analyzing the fiscal forecasting errors of 28 states in India (Working Papers Series WP No. 964). Levy Economics Institute. Chakraborty, L., Kaur, A., Rangan. D., & Farida Jacob, J. (2021). Covid 19 and fiscal-monetary policy responses in Asia Pacific. NIPFP Publications. Filardo, A., & Hans, G. (2010). Monetary policy strategies in the Asia and Pacific region: What way forward? (Working Papers 195/ADBI). Asian Development Bank Institute. Furman, J. (2017). Should policymakers care whether inequality is helpful or harmful for growth? Jason Furman Harvard Kennedy School. Gasper, D. (2002). Is sen’s capability approach an adequate basis for considering human development? Review of Political Economy, 14(4), 435–461. https:// doi.org/10.1080/0953825022000009898 Heine, D., Norregaard, J. & Parry, I. (2012). Environmental tax reform: Principles from theory and practice to date (IMF Working Paper 12/180). International Monetary Fund. Horst, H., Chakraborty, L. S., & Khurana, S. (2017). Fiscal policy, economic growth and innovation: An empirical analysis of G20 countries (Working Paper Archive 883). Levy Economics Institute. International Labour Organization (ILO). (2015). Social protection in Asia and the Pacific and the Arab states. ILO Bangkok. Kaur, A., & Chakraborty, L. (2019). UDAY power debt in retrospect and prospects: Analyzing the efficiency parameters (Working Papers id: 12968), eSocialSciences. https://ideas.repec.org/p/ess/wpaper/id12968.html Kaur, A., Chakraborty, L., & Rangan, D. (2021). Covid-19 economic stimulus and state-level power sector performance: Analyzing the efficiency parameters. Economic and Political Weekly, 56(43). Levinsohn, J., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies, 317–341. Nitin, K., & Roy, R. (2016). Finance commission of India’s assessments: A political economy contention between expectations and outcomes, Applied Journal, 48(2). Raghabendra, C., & Duflo, E. (2001). Women’s leadership and policy decisions: Evidence from a nationwide randomized experiment in India (Working Papers Sereis dp-114). Boston University–Department of Economics. Reserve Bank of India. (2021). Report on currency and finance. Reserve Bank of India. Roy, R., & Heuty, A. (2009). Fiscal space: Policy options for financing human development. Routledge.
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SIPRI. (2017). Yearbook trends in world military expenditure. SIPRI. Stern, N. (2002, January 10). Public finance and policy for development: Challenges for India. Silver Jubilee Lecture. National Institute of Public Finance and Policy (NIPFP). Stiglitz, J., & Rashid, H. (2020, July 31). A global debt crisis is looming: How can we prevent it? Project Syndicate. Tanzi, V. (2016). Review of fiscal consolidation, budget deficits and macroeconomic activity. Sage Publications in Blog, National Institute of Public Finance and Policy. UNESCAP. (2017). Fiscal policy for better health outcomes in the Pacific. UNESCAP. Vinod, H., Karun, H., & Chakraborty, L. (2020). Encouraging private investment in India? In H. Vinod, & C. R. Rao (Eds.), Handbook of Statistics (155–183), Vol. 42. Elsevier.
CHAPTER 3
Gender-Budgeting and Gender Equality Outcomes: Evidence from Asia-Pacific
Assessing the impact of fiscal policy—in particular gender budgeting— on women’s development in the region is complex. Linking gender budgeting to outcomes requires not only assessing the success of gender budgeting in influencing fiscal policies but also assessing the linkage of fiscal policy to gender equality and women’s development (Chakraborty, 2016a; Stotsky, 2020; Stotsky & Zaman, 2016; Stotsky et al., 2019). Since there is a contemporaneous transformation of many socio-economic and policy variables that result in gender-related development, it is a difficult task to establish a link between the fiscal policies specifically and gender-related development (Chakraborty et al., 2018; Lahiri et al., 2002). However, the ability to establish such links would enable us to assess whether government investments, especially in human development and gender budgeting, result in women’s development and more gender equality. Two overarching primary motivations for gender budgeting: its perceived positive impacts on economic efficiency, growth, and productivity, and its positive impacts on equity, both in terms of inclusive development and equal realization of human rights. Growth is often cited as an outcome of reducing gender inequality, which serves to close inefficient gender gaps in workforce participation, education, and health (Berik et al., 2009; Dollar & Gatti, 1999; Esteve-Volart, 2004; Hill & King, 1995; Klasen, 1999; Knowles et al., 2002). However, as many scholars
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_3
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point out, pinning the direction of causality between growth and reduction of gender inequality is tricky (Cuberes & Teignier, ; Stotsky & Zaman, 2016). Literature on gender budgeting often posits the advancement of gender equality and women’s and girls’ development as a motivation for gender budgeting (Sharp & Elson, 2008; Stotsky, 2016). Moreover, governments adopting gender budgeting also highlight the amelioration of gender disparities and the empowerment of women as the key motivation. For example, in Asia, the Indian, South Korean, and Afghan gender-budgeting initiatives all posit women’s advancement as the motivator for their programmes (Chakraborty, 2016b; Kolovich & Shibuya, 2016; Stotsky, 2020). Yet another basic element of gender budgeting is the collection of sex-disaggregated statistics, and several countries have begun their gender-budgeting efforts with a mandate for greater disaggregation of sector-specific statistics (Chakraborty, 2016a; Kolovich & Shubuya, 2016). This sex-disaggregated data can be used to justify the passage of laws addressing gender disparities, such as laws promoting women’s health and safety, access to education, equal rights to work, etc. Using a fixed-effects model of pooled least squares for the early 1990s, Lahiri et al. (2002) find that there is a positive functional relationship between per capita combined expenditure on health and education and the UNDP’s Human Development Index and the associated Gender Development Index. This result confirms that public expenditure on human capital formation, despite the constraints of intra-household disparities in resource allocation, especially on human capital formation, leads to better gender development indicators. Chakraborty (2003) and (2005) examine the link between public expenditure on human development and the Gender Development Index by incorporating economic growth variables. Empirical evidence shows that in a semi-logarithmic framework, regressing proportionate shortfalls of life expectancy against per capita GDP reveals that nearly half of the variations in the life expectancy can be attributed to differences in GNP per head (Anand & Ravallion, 1993). In this context, it is important to note that the substantial impact of higher GDP per head on life expectancy and other social outcomes of better literacy level, low mortality rates among children, and better schooling among children seems to work via factors in which the public policy stance plays a significant part. Chakraborty (2003) and (2005), using fixed effects panel
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estimation, in the context of Asia-Pacific, find that both economic growth and the public policy stance matter for gender-related development, however, public policy variables (expenditure on human development, especially education and health) were more meaningful than economic growth in determining the outcomes for gender-related development. This reinforces the significance of fiscal policy for human development and gender budgeting. A point to be noted here is that the effectiveness of public expenditure on education and health for women and men are different due to the asymmetric scales of socio-economic development. As noted, the evidence from gender-disaggregated benefit incidence analysis revealed that the effectiveness of education and health spending across gender and regions are different. This strengthens the case for gender budgeting in social sectors like education and health. As Stotsky and Zaman (2016) have observed, there have been few efforts to assess the results of gender budgeting in a quantitative manner. Yet most other studies evaluating the success of gender budgeting initiatives tend to focus on the success of their implementation—that is, whether governments are following the steps of gender budgeting, rather than their impact in achieving their goals of equality, growth, inclusive development, and human rights [see, for example, Nakray (2009) and Mushi and Edward (2010)]. Lahiri et al. (2002) using a fixed effects model of pooled least squares for the early 1990s, find that increase in spending on health and education resulted in an increase in Human Development Index (HDI) and GDI for the period between 1993 and 2002. This demonstrates that public expenditure on human capital formation positively impacts gender development indicators. It is important to note that the effectiveness of public expenditures on health and education may vary across regions according to asymmetric scales of socio-economic development (Chakraborty, 2016a, 2016b). Stotsky and Zaman (2016) analysed whether the practice of gender budgeting has yielded greater gender equality in school enrolment (as a proxy for gender equality) and increased spending on social services, education, health, welfare, and infrastructure in Indian states. This chapter seeks to take this literature forward by testing the link between gender budgeting and gender equality outcomes in the context of Asia-Pacific.
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Measuring Gender Equality Globally a data revolution is required to capture the inequalities in gender-sensitive human development, and in turn to construct appropriate measurement indices. This challenge is indeed substantial and methodological. Lately, there are many models that analyse the relationship between gender inequality and economic growth, but the statistics and indices about gender inequalities are not adequate for assessing such empirical links with economic growth (Anand & Sen, 1995; Dijkstra, 2002, 2006; Ferrant, 2009). Beyond measuring aggregate affluence, the United Nations Development Program (UNDP) was the pioneer in constructing gender-related indices. The 1995 Human Development Report (HDR) introduced two gender-based indices—the Gender-related Development Index (GDI) and Gender Empowerment Measure (GEM). These were the first composite indices designed to reflect gender disparities in capability deprivation at a global level and were widely used by many researchers across the globe for studying gender disparities between women and men. In measuring gender-sensitive human development, the economic growth measures used in early empirical literature had constraints in capturing the wider aspects of well-being and the contingent process of development. Noorbakhsh (1998) noted that the criticisms against using economic growth as the proxy for assessing human development can be traced back to the UN Report of 1954. Since then, the array of literature in favour of using social indicators to measure human development has resulted in the collation of data on a spectrum of socio-economic indicators across countries, which has inevitably resulted in attempts to construct composite indices of human development and gender inequality (Adelman & Morris, 1967; Hicks & Streeten, 1979; Morris, 1979; UNDP, 1995; UNRISD, 1972). To analyse the link between fiscal policy and gender equality, the measurement issues relate to the latter are crucial. GDP is no longer a proxy for human development. The Human Development Index (HDI) is a gender-neutral index of the basic capabilities in three dimensions of human development: the geometric mean of selected dimensions of health, education, and income. The process of enlarging people’s choices and raising the level of wellbeing is defined as human development. Conceptually, these choices can be infinite. These choices can vary intertemporally and spatially. From the infinite set of choices, UNDP had selected three dimensions as the most
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critical and socially valuable: the ability to lead a long and healthy life; the choice to acquire knowledge and be educated; and access to resources needed for a decent level of living (UNDP Human Development Reports, various years). The Gender Development Index (GDI) was constructed in 1995 by the UNDP to measure gender development. The GDI used the same variables as HDI, but adjusted for the degree of disparity in achievement across genders. The average value of each of the component variables is substituted by “equally distributed equivalent achievements.” The equally distributed equivalent achievement (X ede ) for a variable is taken as the level of achievement that, if attained equally by women and men, would be judged to be exactly as valuable socially as the actually observed disparate achievements. Lahiri et al. (2002) noted that taking an additively separable, symmetric, and constant elasticity marginal valuation function with an elasticity of 2, the equally distributed equivalent achievement X ede for any variable X turns out to be as follows: X ede = [n f (1/ X f ) + n m (1/ X m )]−−1 where X f and X m are the values of the variable for females and males, and n f and n m are the population shares of females and males. X ede is a “gender-equity-sensitive indicator” (GESI). Thus, for this chosen value of 2 for constant elasticity marginal valuation function, GDI is computed as follows: GDI = {L ede + (2/3 × Aede + 1/3 × E ede ) + Yede }/3 The Inequality Adjusted Human Development Index (IHDI) adjusts the HDI for inequality in each dimension across the entire population. Like HDI, it is calculated using the geometric mean but using inequalityadjusted dimension indices. The IHDI takes into account achievements in terms of health, education, and income by discounting each dimension’s average value according to its level of inequality. Under perfect equality, HDI will equal IHDI. In cases of inequality, IHDI will fall below HDI. The difference between IHDI and HDI is the loss of human development due to inequality. IHDI is calculated for 145 countries by the UNDP. Life expectancy is distributed across a group of subjects who have shared a particular event distribution presented over different age intervals, whereas years of schooling and income are distributed across individuals.
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The inequality measure, A, is defined as 1− µg where g is the geometric mean and µ is the arithmetic mean of the distribution. Symbolically, √ n X 1 . . . ..X n Ax = 1 − X Owing to the conceptual and methodological problems identified by researchers in the calculation of these indices, the 2010 HDR introduced a new measure of gender inequality, the Gender Inequality Index (GII). This index was designed to capture women’s disadvantages in three dimensions—reproductive health, empowerment, and economic activity. It reflects the loss in achievement due to inequality between men and women. An index of 0 implies that both the genders fare equally in all three select dimensions, whereas an index of 1 implies complete inequality. Gender Inequality Index (GII), which replaced the GDI in 2010, reflects gender-based disadvantage in mainly three dimensions: reproductive health, proxied by maternal mortality ratio (MMR) and adolescent fertility rate (AFR); empowerment, as proxied by the share of parliamentary seats held across gender (PR) and attainment of secondary education (SE); and economic activity is proxied by the labour market participation rate (LFPR), which measures the participation of men and women in the market economy. The maternal mortality rate is defined as the number of female deaths per 100,000 live births annually, from any cause related to, or aggravated by, pregnancy or its management. AFR is the number of births per 1000 women aged 15–19. GII reflects the loss in development due to inequality across genders. An index of 0 implies women and men fare equally whereas an index of 1 implies that one of the two genders fares as poorly as is possible. The first step in the calculation of GII involves treating zeros and extreme values (i.e. the outliers). GII is calculated by taking the geometric mean across the dimensions; because the geometric mean cannot be calculated for zero values, a minimum of 0.1 per cent is set for all the components. The maximum value for the maternal mortality rate is taken as 1000 deaths per 100,000 births and the minimum value is 10 per 100,000 births. A higher maternal mortality rate suggests poor maternal health. After treating zeros, if any, we aggregate across dimensions within each gender group using geometric means. As the reproductive health variables
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are used, the aggregation formula for men and women is different. ⎡/
| | 1 10 3 | Gf = . . (PRf.SEf).LFRPf MMR AFR The rescaling by 0.1 is required to take into account the truncation of the maternal mortality ratio minimum at 10. For males, the formula is as follows: /
Gm = 3 1. (PRm.SEm).LFRPm Once the geometric mean of the three dimensions that determine the inequality index is taken, the next step is to aggregate across gender using the harmonic mean. The argument for using the harmonic mean is that it captures the inequality between women and men and further adjusts for the association between dimensions, but this method is open to criticism (Hawken & Munck, 2013). The Harmonic Mean (HARM) index is as follows:
⎞−1 ⎛ (Gf)−1 + (Gm)−1 ⎠ HARM(Gf, Gm) = ⎝ 2 Before calculating the final index, a composite index is calculated using the geometric means of the arithmetic means; this step is to give equal weights to both genders. We then aggregate it across the various dimensions, i.e. health, empowerment, and economic activity. The composite index is as follows: /
G f,m =
3
Health.Empowerment.LFPR
Where
/ (
1 10 MMR . AFR
)
Health=
Empowerment =
+1
2
√ (PRf.SEf) + (PRm.SEm) 2
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LFPR =
(LFPRf + LFPRm) 2
Symbolically, the GII is as follows: GII = 1−
HARM(Gf,Gm) G(f,m)
The higher the value of GII, the higher the gender gap and the loss in the potential for human development. Hence in order to utilize all our resources fully, we need to bridge this gender gap. Hawken and Munck (2013) pointed out data availability was not seen as a constraint for the construction of GII and that new data can be generated to measure certain indicators that are considered central to an index’s overarching concept. However, Permanyer (2013) points out, that an increase in MMR and AFR systematically represents an increase in gender inequality levels while, on the other hand, decreases in women’s education or labour force participation rates (LFPR) do not necessarily represent a worse state of affairs as long as men’s education and LFPR decrease by the same amount. Also, the corresponding value of MMR and AFR for men is taken as 1, which is far from realistic and leads to overestimation of the gap between women’s and men’s health standards. Yet another problem with using indicators like reproductive health is that it penalizes low-income countries, as health standards are usually low in developing countries. While the proponents of the index might rightly argue that it makes sense to penalize those countries with bad reproductive health conditions for women, it is fair to say that a country’s performance in those areas is influenced by a myriad of factors other than gender-related issues (Permanyer, 2013). This calls for variables that are broader and capture the health standards of both the sexes equally. The third sub-indicator of the GII is LFPR, which measures the involvement of men and women in paid work. We know that housework, childcare, and care of elderly relatives represent women’s unpaid work—which is an indispensable financial benefit to the entire economy (Bartuskova & Kubelkova, 2014)—yet it fails to capture the care economy where women are typically overrepresented. Owing to the importance of unpaid work and the differences in the representation of genders in Systems in National Accounts (SNA) and non-SNA activities, it is desirable to incorporate unpaid work into the gender inequality index.
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Aggarwal and Chakraborty (2015) highlight the shortcomings of GDI and GII as none of the measures address the statistical invisibility of the care economy.
Interpreting Data Asian countries encompass a range of levels of development and show differing degrees of gender inequality, with most falling into the middle or lower-income categories. Asian countries have generally been making progress in addressing gender inequality and women’s advancement, even though gender inequality remains high. Figure 3.1 shows gender inequality in secondary education, where we can see that the trend is towards greater equality. Figure 3.2 shows gender inequality in under 5 mortality, where boys have a natural disadvantage. The high female to
Fig. 3.1 Gross secondary enrolment ratio in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates)
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Fig. 3.2 Under 5 child mortality in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates)
male ratio in India is notable, which skews the natural advantage of girls in survival and missing women estimates (Anderson & Ray, 2010; Klasen, 1994; Klasen & Wink, 2003). Figure 3.3 shows maternal mortality, a key indicator of women’s advancement, and the almost universal trend in the region of declining mortality, even while maternal mortality remains high in many countries (Thaddeus & Maine, 1994; van den Broek & Falconer, 2011). Figure 3.4 shows gender gaps in labour force participation rates, ages 15–64 (female to male ratio), where the trend is towards equality, though notably, a number of countries show a declining ratio (Fig. 3.5). While individual indicators are illustrative of developments in key variables, gender equality indices provide a useful summary of an aggregation of indicators. Figure 3.6 presents a summary of the Gender Development
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Fig. 3.3 Maternal mortality ratio in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates)
Index (GDI) across the region for the latest year for which data are available. This index generally ranges from 0 to 1, where higher numbers represent more equality. The range of results suggests that the region as a whole has made progress in recent decades. Advanced countries in the region and some of the developing countries are doing better overall, while the south Asian countries clearly tend to lag.
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Fig. 3.4 Labour force participation rate in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates)
The Empirical Investigation Gender equality (GE) is captured in the models by Gender Development Index (GDI) and Gender Inequality Index (GII). Under the GDI, the average value of each of the component variables in the index— education, health, and income—is substituted with “equally distributed equivalent achievements” (Lahiri et al., 2002). The equally distributed equivalent achievement (X ede ) represents the level of achievement that would, if attained equally by women and men, be considered exactly as valuable to society as the actually observed disparate achievements. The
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Fig. 3.5 Women in national parliaments in Asia-Pacific (Source World Bank, World Development Indicators database; and authors’ estimates)
GII is a measure of disparities between the genders across three dimensions: (i) reproductive health, represented by the maternal mortality ratio (MMR) and the adolescent fertility rate (AFR); (ii) women’s empowerment, represented by the proportion of parliamentary seats held by each sex (PR) and the sexes’ rates of attainment of secondary education (SE); and (iii) economic activity, represented by the labour force participation rate (LFPR) of men and women in the market economy. The GII shows the loss in development resulting from gender inequality, where a score of 0 represents complete equality and a score of 1 implies complete
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Fig. 3.6 GDI, time consistent version (Source Authors’ estimates)
inequality. The model we consider for analysis is GEit = a + b 1 GBit + b 2 X it + µit , where we test whether gender budgeting (GB) is a significant determinant of gender equality (GE) in the Asia-Pacific region, along with control variables (X ). The control variables we use in our models are the log of public spending on health and education, GDP per capita, and female labour force participation. The dynamic panel estimates in Table 3.1 show that gender budgeting is significantly and positively related to the GDI in the Asia-Pacific countries. In the dynamic panel model, public spending on health and education, as well as growth, are found to be insignificant in determining the GDI. The results also show that the GII is significantly determined
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Table 3.1 Determinants of GDI, GII, and sectoral spending: panel estimates Variables
Model (1) GDI
Model (2) GII
Lagged GDI
0.7711* (10.5700) 0.0001 (0.8300) 0.0019 (1.6200) 0.0004 (0.2800) –
0.7167* (0.0571) 0.0000 (0.0000) –0.0041* (0.0017) 0.0031 (0.0022) –
–0.0011 (–0.7400) –
–0.0045* (0.0024) –
0.0024* (3.1100)
–0.0035* (0.0008)
Log of GDP per capita Female labour force participation rate Log of public spending on education Log of public spending on education (lag) Log of public spending on health Log of public spending on health (lag) Gender budgeting in call circular regime Female literacy rate Maternal mortality rate Constant
– –1.8669* (–3.1300)
– 2.9819* (0.6693)
Model (3) (Health) – 0.0001* (0.0000) – – – – 0.6795* (0.0447) –0.0068 (0.0167)
0.0017* (0.0007) 6.3525 (14.4790)
Model (4) (Education) – 0.0020* (0.0010) – – 0.7065 (0.5473) 0.8933 (0.5774) – 0.1982 (0.3511) –0.1893* (0.0991) – –172.6384 (297.4006)
* 1 % level of significance Note The figures in the brackets refer to standard errors Source UN Human Development Reports, IMF Gender Database, and World Development Indicators (various years, basic data)
by gender-budgeting initiatives, public spending on health, and female labour force participation. Spending on education and economic growth variables are found to be insignificant in reducing the GII. The estimates showed that public health spending in the Asia-Pacific region and GII are inversely related. Also, an increase in female labour force participation can reduce the GII in the region. Against a backdrop of fiscal consolidation and rule-based fiscal policy, countries in the Asia-Pacific region are increasingly adhering to a 3 per cent ratio of fiscal deficit to GDP. In India, the Fiscal Responsibility and Management Act has recommended that national and subnational governments adhere to a debt–GDP ratio of 60 per cent. In determining education and health sector expenditure, could gender budgeting be
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a determinant? To analyse this, we have examined sectoral patterns in public spending in education and health, and examined whether gender budgeting has any impact on public spending on these sectors. The dynamic panel estimates in Table 3.1 reveal that gender budgeting is found to be insignificant in increasing fiscal spending on health (Model 3). We used the MMR to proxy the gender-related health indicator, which was found to be significant in determining fiscal spending on health. Public spending on health does increase with an increase in economic growth. The dynamic panel estimates, following the methodology of Arenallo and Bond (1991), show that gender budgeting does not have an impact on education spending (Model 4). Moreover, the impact of gender budgeting on aggregate expenditure has not been attempted, as the sectoral inferences are insignificant. Overall GDP and the sectoral outcome indicators are found to be the determinants of sectoral spending.
The Significance to Go Beyond Models The empirical evidence reveals that gender-budgeting efforts have a more significant impact on gender-equality-sensitive indices as compared to economic growth. Public policy variables, like public spending on health and education, were also found to be relevant for the progress of gender equality in the region. The analysis showed the impact of gender budgeting on increasing fiscal spending in health and education, using the MMR as a proxy for health and the gender disparity ratio in education as a proxy variable for education outcomes. The implications of gender budgeting in these areas were insignificant. This has public policy implications, against the backdrop of fiscal rules, as the countries in the Asia-Pacific region have not yet incorporated gender budgeting as a priority in their spending decisions. The limited purpose of the chapter is to analyse the growth versus public spending variables on gender equality outcomes. The results need to be read with caution as the variables relate to intra-household variables and gender-specific behaviour variables are not included in the models in analyzing the gender equality outcomes. As Nelson (2017) pointed out, the gender differences in behaviour are socially constructed than naturally, which in turn affects the education, leadership, and employment outcomes. As Christine Lagarde (former Managing Director of IMF) asked, if Lehman Brothers (the first bank to fail in the USA) had been Lehman Sisters would there have been a crisis? This remark was made partly in jest (Perrons, 2018),
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but nonetheless, it implied that rather than there being any problems with the financial system of neoliberalism, the crisis was due to the overexuberance of the testosterone-driven macho men of Wall Street whose risky behaviour might have been curbed by the presence of more “naturally” risk-averse women (Prugl, 2012). This view suggests the limitations of existing empirical research and the requirement to unpack the models in behavioural economics because the findings are more nuanced and complex. This is beyond the scope of this book, however, that sets the agenda for further research in empirical gender economics.
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Chakraborty, L. (2016b). Fiscal consolidation, budget deficits and macroeconomy: Monetary-fiscal linkages. Sage Publications. Cuberes, D., & Teignier, M. (2012). Gender gaps in the labor market and aggregate productivity (Sheffield Economic Research Paper (SERP) Number 2012017). Cuberes, D., & Teignier, M. (2014). Gender inequality and economic growth: A critical review. Journal of International Development, 26, 260–276. Chakraborty, L., Ingrams, M., & Singh, Y. (2018). Fiscal policy effectiveness and inequality: Efficacy of gender budgeting in Asia Pacific (Working Paper No. 224). National Institute of Public Finance and Policy. Dijkstra, A. G. (2002). Revisiting UNDP’s GDI and GEM: Toward an alternative. Social Indicators Research, 57 , 301–338. Dijkstra, A. G. (2006). Towards a fresh start in measuring gender equality: A contribution to the debate. Journal of Human Development, 7 , 275–283. Dollar, D., & Gatti, R. (1999). Gender inequality, income, and growth: Are good times good for women? (Working Paper Series 1). World Bank Policy Research Report on Gender and Development, World Bank. Esteve-Volart, B. (2004). Gender discrimination and growth: Theory and evidence from India (Development Economics Papers 42), The Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics. Ferrant, G. (2009). A new way to measure gender inequalities in developing countries: The gender inequalities index (GII) (CEAFE Papers). http://www.tn. auf.org/CEAFE/Papiers_CEAFE10/MacroI/Ferrant.pdf Hawken, A., & Munck, G. L. (2013). Cross-national indices with genderdifferentiated data: What do they measure? How valid are they? Social Indicators Research, 111(3), 801–838. Hicks, N., & Streeten, P. (1979). Indicators of development: The search for a basic needs yardstick. World Development, 7 , 567–580. Hill, M. A., & King, E. (1995). Women’s education and economic wellbeing. Feminist Economics, 1(2), 21–46. Klasen, S. (1994). Missing women reconsidered. World Development, 22, 1061– 1071. Klasen, S. (1999). Does gender inequality reduce growth and development? Evidence from cross-country regressions. Policy Research Report on Gender and Development. World Bank. Klasen, S., & Wink, C. (2003). Missing women: Revisiting the debate. Feminist Economics, 9, 263–299. Kolovich, L., & Shibuya, S. 2016. Middle east and central Asia: A survey of gender budgeting efforts (IMF Working Papers 16/151). IMF.
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Knowles, S., Lorgelly, P., & Owen, P. D. (2002). Are educational gender gaps a brake on economic development? Some cross-country empirical evidence. Oxford Economic Papers, 54(1), 118–149. Lahiri, A., Chakraborty L., & Bhattacharyya, P. N. (2002). Gender budgeting in India. Follow the Money Series. UNIFEM. Morris, M. D. (1979). Measuring the condition of the world’s poor: The physical quality of life index. Pergamon. Mushi, V., & Edward, M. (2010). Challenges and successes of gender budgeting initiatives: A case study of Tanzania. Accountancy and Business Review Journal, 7 (2), 19–24. Nakray, K. (2009). Gender budgeting: Does it really work? Some experience from India. Policy and Politics, 37 (2), 307–310. Nelson, J. A. (2017). Gender and risk-taking: Economics. Routledge. Noorbakhsh, F. (1998). A modified human development index. World Development, 26(3), 517–528. Permanyer, I. (2013). A critical assessment of the UNDP’s gender inequality index. Feminist Economics, 19(2), 1–32. Perrons, D. (2018, July). Review of gender and risk-taking: Economics, evidence, and why the answer matters. Gender and Development, 26(2). Prugl, E. (2012). “If Lehman brothers had been Lehman sisters…”: Gender and myth in the aftermath of the financial crisis. International Political Sociology, 6(1), 21–35. Sharp, R., & Elson, D. (2008). Improving budgets: A framework for assessing gender responsive budget initiatives. Hawke Research Institute for Sustainable Societies, University of South Australia. Stotsky, J. G. (2016). Gender budgeting: Fiscal context and overview of current outcomes (IMF Working Paper 16/149). International Monetary Fund. Stotsky, J. (2020). Using fiscal policy and public financial management to promote gender equality international perspectives. Routledge. Stotsky, J., & Zaman, A. (2016). The influence of gender budgeting in Indian states on gender inequality and fiscal spending (International Monetary Fund Working Paper 16/227). Stotsky, J., Chakraborty, L., & Gandhi, P. (2019). Impact of intergovernmental fiscal transfers on gender equality in India: An empirical analysis (Working Paper). National Institute of Public Finance and Policy. Thaddeus, S., & Maine, S. (1994, April). Too far to walk: Maternal mortality in context. Social Science and Medicine, 38(8), 1091–1110. United Nations Development Programme (UNDP). (1995). Human development report. UNDP. United Nations Research Institute for Social Development (UNRISD). (1972). Contents and measurement of socio-economic development. Praeger Publishers.
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Van den Broek, N. R., & Falconer, A. D. (2011). Maternal mortality and millennium development goal 5. British Medical Bulletin, 99, 25–38. (Working Paper No. 273).
CHAPTER 4
Gender Budgeting and the Efficacy of Measuring Unpaid Care Economy
Gender budgeting is a tool of accountability that provides thrust to the unpaid care economy, which is otherwise statistically invisible. It is not just confined to specifically targeted programmes for women in the existing budget. Measuring the unpaid care economy is a unique contribution to the economic literature and policy discourses as it captures the roles and well-being of children, women, and men, especially poor women and mothers, in ways that extend beyond the scope of standard economic indicators (Grown et al., 2010). In the theory of the allocation of time, the allocation and efficiency of nonmarket working time may be more important to economic growth than market working time. Yet, the attention paid by economists to the market economy skews any paid to the other; nonmarket work continues to remain statistically invisible. Timeuse data is used to capture the chronology of time, in which the time is dichotomized into market time and nonmarket time. The impact of the crisis on unpaid care economy work has been conducted against the backdrop of the global financial crisis (Bahçe-Kaya & Memi¸s, 2013; Berik & Ebru, 2013; Floro & Hitomi, 2011; Yamamoto, 2017) and recently ex post to COVID-19 pandemic outbreak (Andrew et al., 2020; ˙ & Emel, 2021). Chakraborty et al., 2021; Deshpande, 2020; Ilkkaracan
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_4
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Against the backdrop of COVID-19 pandemic, the time-use surveys are becoming more relevant to capture the fragility of work–life balance of employed women and the plausible window of opportunity created by men’s increased participation in unpaid work (Andrew et al, 2020; ˙ Ilkkaracan & Emel, 2021). In the context of Turkey, during the COVID19 pandemic, women’s unpaid work time almost doubled, while men’s ˙ quadrupled. Ilkkaracan and Emel (2021) highlighted the need for work– life balance policies and for investment in social care economy infrastructure in times of covid19. In India, Deshpande (2020) has analysed the first-order effects of lockdown on gender gaps in time allocation and in turn labour market outcomes. Chakraborty (2021) has analysed the gender components of economic stimulus packages—both fiscal and monetary policies—of selected countries in the Asia–Pacific region and identified that care economy infrastructure has not been given adequate emphasis in the stimulus packages in the region. The data from rapid gender assessment surveys investigating the socioeconomic consequences of COVID-19 on women’s and men’s lives, reveals that the impact of the pandemic goes far beyond health consequences (Seck et al., 2021); and given the labour markets in turmoil, work from home with young children out of school and intensified care needs of elderly and ill family members, there is a significant increase in the demand for unpaid domestic and care work during the COVID-19 pandemic. The study noted that with the market economy being closed, women are disproportionately bearing the burden of unpaid care and domestic work triggered by the lockdowns, and they are losing their livelihoods faster than men, and women are disproportionately affected by mental health issues (Seck et al., 2021). Craig and Brendan (2021) report early results on how the pandemic affected paid work, domestic work, and caring responsibilities. Their findings revealed that women shouldered most of the extra unpaid workload, but men’s childcare time increased more in relative terms, so average gender gaps narrowed. These inferences reflect a need for sustained policy attention to the care economy to narrow rather than widen gender disparity during the time of pandemic. Gender budgeting is a promising fiscal framework to incorporate these significant concerns related to the unpaid care economy.
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Statistical Invisibility of Unpaid Care Economy In theory, the nonmarket time aggregates leisure and work at home. The justification for aggregating leisure and unpaid work at home rests on two assumptions: (a) the two elements react similarly to changes in the socio-economic environment and, therefore, nothing is gained by studying them separately; and (b) the two elements satisfy the conditions of a composite input—that is, the relative price is constant and there is no interest in investigating the composition of the aggregate since it has no bearing on production and the price of the output (Gronau, 1977). However, the time-use survey findings did reveal that these two assumptions are wrong, as unpaid work at home and leisure are not affected in the same way by changes in socioeconomic variables and the composition of the aggregate affects many facets of the intrahousehold behaviour. The findings from time-use survey—tricotomising the allocation of time into work in market, work at home, and leisure— can provide insights to integrate the nonmarket work into economic modelling and, in turn, in macroeconomic policymaking. This is particularly relevant when public investment policy can redress intra-household inequalities in terms of household division of labour by supporting initiatives that reduce the time allocation of women in unpaid work. Examples of such public policy interventions are improved infrastructure in the water sector, rural electrification, roads, sanitation services, and better transport infrastructure. Despite the growing recognition of implications of time-budget statistics for macroeconomic policymaking, there have been relatively few examples of empirical literature on the topic. Bredie and Beeharry (1998) revealed that easy accessibility to drinking water facilities might lead to an increase in school enrollment, particularly for girls; in Madagascar, 83 per cent of the girls who did not go to school spent their time collecting water, while only 58 per cent of the girls who attended school spent time collecting water. Khandker (1988) showed that it was not the patriarchy per se that restricts women’s time from market work in Bangladesh, but rather economic factors like low wages and low education. In the context of Pakistan, Ilahi and Franque (2000) indicated that worsening water-gathering infrastructure caused an increase in the total work burden of women. Empirical evidence suggests that women workers in Thailand experience a higher incidence of work intensity and
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hence lower quality of life compared with men (Floro & Anant, 2010). Using time-use data, analysis of “time poverty” (defined as lack of enough time for rest and leisure after accounting for the time that has to be spent working, whether in the labour market, doing domestic work, or performing other activities such as fetching water and wood) and found that women are more likely to be “time poor” than men (Bardasi & Quentin, 2010; Gammage, 2010). Motiram and Lars (2010) use the Indian Time Use Survey (ITUS, 1999) to analyse gender inequalities in the allocation of household tasks among girls and boys and their parents, finds more mixed evidence regarding gender favoritism in human capital investment. Liu Lan and Xiao-yuan Dong, Xiaoying Deng, 2010 unveil striking differences in labour market outcomes between caring for parents and caring for parents-in-law: caring for parents does not affect the caregiver’s employment status and work hours, whereas caring for parents-in-law has a statistically significant, sizable, negative effect on the caregiver’s probability of employment and hours of paid work. John (2020) analysed the link between women’s paid work participation and intimate partner violence and found that in Nepal, the evidence refutes the economic bargaining models which contend that women’s paid work reduces violence experienced due to increased bargaining power. The study found that in a traditional setting, working women are more likely to experience increased violence as they transgress traditional gender roles and the underlying gender hierarchies. Nonmarket work remains significantly invisible in national accounts. A recognized shortcoming of the present system of national accounting (SNA) is the omission of nonmarket production from national accounts (Chakraborty, 2014; Mullan, 2010). The attempt of the United Nations Statistical Division in extending the production boundary of the Systems of National Accounts (SNA) in 1993 has led to the inclusion of nonmarket work into the national accounting system as satellite accounts (Box 4.1). Based on SNA 1993, the TUS classified the activities into SNA activities (that get included in GDP calculations), non-SNA activities (that do not get included in GDP but should be included in the satellite accounts), and residual activities. In the Time Use Survey conducted in India by the National Statistical Organisation, the International Classification of Activities for Time Use Statistics 2016 (3-digit code) (ICATUS) was used to record the activities of the household members. The classification of activities in System of National Accounts (SNA) Production, non-SNA, and other remaining activities is given in the Box 4.2.
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Box 4.1: Time-Use Survey classification of activities in SNA and NonSNA, India 2020
• SNA production • Employment in corporations, government and non-profit institutions • Production of goods for own final use • Employment in household enterprises to produce goods • Employment in household enterprises to provide services • Ancillary activities and breaks related to employment • Training and studies in relation to employment • Employment-related travel • Unpaid trainee work and related activities • Unpaid direct volunteering for other households for production of goods or for production of goods/services for market/non-market units • Unpaid community- and organization-based volunteering for production of goods or for production of goods/services for market/non-market units • Other unpaid work activities (other than those which are already covered in SNA or covered in non-SNA production) • Non-SNA production • Unpaid domestic services for household members • Unpaid caregiving services for household members • Unpaid direct volunteering for other households for production of services for the Households • Unpaid community- and organization-based volunteering for production of services for the Households • Other residual activities • Seeking employment • Setting up a business • Commuting • Learning • Socializing and communication, community participation and religious practice • Culture, leisure, mass-media and sports practices • Self-care and maintenance
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Source Government of India (2020), Time Use Survey 2020, National Statistical Office
Box 4.2: Systems of National Accounts 1993
The 1993 System of National Accounts (SNA) limits economic production of households for their own consumption to the production of goods alone and excludes the own-account production of personal and domestic services (except for the services produced by employing paid domestic staff, the own-account production of housing services produced by employing paid domestic staff, and the own-account production of housing services by owneroccupants). This allows the SNA to avoid valuing activities such as eating, drinking, and sleeping, which are difficult for a person to obtain from another person. But, in the process, activities such as fetching water from the river or the well, collecting fuel wood, washing clothes, house cleaning, and preparation and serving of meals, as well as care, training, and instruction of children and care of sick, infirm, or old people also gets excluded from the definition of economic activity. These services are mostly performed by women, but can also be procured from other units. While these activities are excluded partly because of the inadequate price systems for valuing these services, this exclusion principle leads to the economic invisibility and a statistical underestimation of women’s work. It is interesting to recall in this context the famous economist Pigou’s comment that if a housemaid employed by a bachelor were to marry him, national income would fall, since her previously paid work would now be performed unpaid SNA 1993 suggests development of estimates for the value of household production of services for own use in satellite accounts of an alternative concept of gross domestic product (GDP). Estimation of the “unpaid” work of women in the care sector can suggest a quantification of the contribution of women to the economy. The quantification can also be useful for two more reasons. First,
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it would provide a fuller understanding of how resources and time are allocated in the economy. Second, it would indicate the extent to which economic development and the associated feminization of labor—through the substitution of own-account production of services by purchases from the market (for example, households using self-service laundry services instead of washing at home)— would give a fillip to the growth rate of GDP as it is measured. Monitoring such estimates over time can also help in understanding the effect of policies on these own-account production of services, which are critical for welfare Source Systems of National Accounts, UNSD (1993), Lahiri et al. (2002), Chakraborty (2014).
The latest Time Use Survey (TUS) of India was conducted from January to December 2019, for each member of age 6 years and above of the selected 1,38,799 households (rural: 82,897 and urban: 55,902). The Time Use Survey covered 4,47,250 persons of age 6 years and above, with 2,73,195 in rural India and 1,74,055 in urban India. The TUS 2020 noted that the survey covered the whole of the Indian Union except the villages in the Andaman and Nicobar Islands which are difficult to access. The first large-scale survey time-use survey conducted in India from July 1998 to June 1999 covered 18,591 households in India, covering all members of the household aged six years and above, for only six selected States. The Time Use Survey gives a better understanding of how time is allocated across gender in the economy and provides some insights into the extent of statistical invisibility of women’s work in India. The time allocation of different activities under the unpaid care economy sector is highlighted in the analysis in this section. The estimates of latest Time Use Survey are used for the analysis, however, the State-level estimates of the first Time Use Survey are selectively used for valuation of care economy as per cent of Gross State Domestic Product due to required data availability for the valuation. The time-use data is generated usually on the basis of the time-diary method, confined to a probability sample of all types of days (weekdays and weekends). Time diary is a retrospective method in which the respondents are asked to keep an account of a recent twenty-four hours
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chronology of the use of time and researchers code the responses to a standard list of activities. Time-use diaries are preferred over the other methods, for they tend to be more comprehensive, they enable respondents to report activities on their own terms, and they have some form of a built-in check that increases the reliability of the data (Juster & Stanford, 1985). The time-diary method has certain deficiencies. The significant one is the presence of multitasking or omission of overlapping activities. This results from the imposition of a rigid constraint of time use, namely, no person has either more or less time available than twenty-four hours per day (time constraint), and the set of activities capable of being measured, described, and analysed must add up to a fixed number of hours or days (Floro, 1995). Theoretically, it can be solved by defining the new activity as a joint activity, but the codes for possible diary activities would explode in number. The practical way of solving this problem is to indicate one activity as primary and the other as “secondary”. Yet another way to conceptualize secondary activities is to argue that there is only one activity at any given time, but there are frequent switches between activities and if the time grid were fine enough, the issue of secondary activities would effectively disappear. Finally, it seems plausible that the issue of multiple or joint activities is the key source of the major failure of alternative recall methods. Recall accuracy falls when the respondents make primitive attempts to respond to questions about hours of an activity in the last week or month by engaging in a kind of temporal double counting — adding in periods when the activity was secondary to periods when it was central (Juster & Stanford, 1985).
Time-Use Pattern Across Gender and Geography in India The estimates of time use per day in different activities are presented in this section for the Indian context, considering the participants in different activities and also presented considering all persons irrespective of their participation in activities to understand the distribution of total time of 1440 minutes available for each person in a day in different activities (Government of India, Time Use Survey, 2020). The participation rate in a day in any activity is defined in the Time Use Survey as the
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percentage of persons performing that activity during the 24 hours of the reference period. The average time (in minutes) spent in a day per person in SNA production, non-SNA productions, and residual other activities in India is given in Table 4.1. In rural India, women spent 286 minutes (around 5 hours) while men spent only 40 minutes a day. In urban India, men spent only half an hour in the care economy, while women spent 270 minutes a day (Table 4.1). The percentage share of SNA production, non-SNA production, and residual other activities of the total time in a day per person based on India is given in Table 4.2. The estimates reveal that 19.9 per cent of time spent by women in the care economy in rural India is compared to Table 4.1 Time allocation in SNA and Non-SNA, India 2020 Description of the activity (all India)
SNA production Non-SNA production SNA and non-SNA production Residual other activities Total SNA production Non-SNA production SNA and non-SNA production Residual other activities Total SNA production Non-SNA production SNA and non-SNA production Residual other activities Total
Male Rural 262 40 301 1139 1440 Urban 288 33 321 1119 1440 Aggregate 269 38 307 1133 1440
Female
Person
87 286 373 1067 1440
176 161 337 1103 1440
63 270 333 1107 1440
179 148 327 1113 1440
80 281 361 1079 1440
177 157 334 1106 1440
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 1440 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
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Table 4.2 Distribution (%) of time use into SNA and Non-SNA, India 2020 Description of the activity (all India)
SNA production Non-SNA production SNA and non-SNA production Residual other activities all SNA production Non-SNA production SNA and non-SNA production Residual other activities all SNA production Non-SNA production SNA and non-SNA production Residual other activities all
Male Rural 18.2 2.8 20.9 79.1 100.0 Urban 20.0 2.3 22.3 77.7 100.0 Aggregate 18.7 2.6 21.3 78.7 100.0
Female
Person
6.0 19.9 25.9 74.1 100.0
12.2 11.2 23.4 76.6 100.0
4.4 18.8 23.1 76.9 100.0
12.4 10.3 22.7 77.3 100.0
5.6 19.5 25.1 74.9 100.0
12.3 10.9 23.2 76.8 100.0
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
2.8 per cent by men. In urban India, it is slightly reduced to 18.8 per cent by women and 2.3 per cent by men (Table 4.2). The average time (in minutes) spent in a day per person of different age groups in SNA production, non-SNA production, and residual other activities reveal that in rural India, women even in the age group 60 years and above spent around 217 minutes a day in unpaid care economy sector while men spent 52 minutes a day. In urban India, women and men in the age group, 60 years and above spent 204 minutes and 48 minutes, respectively, a day. The estimates of other age groups suggest that women spent around 5 hours a day in the care economy (Table 4.3). The percentage share of unpaid activities, paid activities, and residual other activities of the total time in day per person of different age groups
SNA production Non-SNA production SNA and non-SNA production Residual other activities All
SNA production Non-SNA production SNA and non-SNA production Residual other activities All
15–59 Years Female
62 332 393
1047 1440 58 265 323
1117 1440
15–29 Years Male
Rural 244
35
280
1160
1440 Urban 255
28
284
1156
1440
1440
1137
303
142
161
1440
1103
337
186
151
Person
60 Years +
Age group (time in minutes)
1440
1049
391
35
356
1440
1068
372
44
327
15–29 Years Male
1440
1045
395
318
77
1440
992
448
345
104
15–59 Years Female
1440
1047
393
173
220
1440
1029
411
196
215
Person
60 Years +
Age-disaggregated time allocation in SNA and Non-SNA in India, 2020
Description of the activity (all India)
Table 4.3
1440
1231
209
48
161
1440
1165
275
52
222
15–29 Years Male
1440
1203
237
204
33
1440
1143
297
217
80
15–59 Years Female
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
(continued)
1440
1217
223
125
98
1440
1155
285
132
154
Person
60 Years +
4
73
312 373
1067 1440
281
1159
1440
60
33
Aggregate 248
15–59 Years Female
1440
1113
327
172
155
Person
60 Years +
1440
1062
378
41
337
15–29 Years Male
1440
1008
432
337
95
15–59 Years Female
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
SNA production Non-SNA production SNA and non-SNA production Residual other activities All
15–29 Years Male
Age group (time in minutes)
(continued)
Description of the activity (all India)
Table 4.3
1440
1035
405
189
217
Person
60 Years +
1440
1185
255
51
204
15–29 Years Male
1440
1161
279
213
65
15–59 Years Female
1440
1173
267
130
136
Person
60 Years +
74 L. S. CHAKRABORTY
4
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
75
reveal that women in the age group 60 years spent 15.1 per cent and 15– 29 years age group spent 23.1 per cent in care economy in rural India, when compared to men of same age groups, respectively, 3.6 per cent and 2.4 per cent of entire day (Table 4.4). The pattern is the same for urban India as well. The average time (in minutes) spent in a day per participant in different activities reveals that women in rural India spent 301 minutes on an average in unpaid domestic services including household chores while men spent only 98 minutes. In urban India, time allocation in household chores by men and women respectively was 97 and 299 minutes. In addition to household chores, women spent 132 minutes on the unpaid caregiving services within the household compared to 77 minutes by men in rural India. In urban India, the time allocation by men and women in unpaid care services was, respectively, 75 and 138 minutes, as per the time-use statistics 2020 (Table 4.5). The average time (in minutes) spent in a day per participant of different levels of education reveals that despite the levels of education, the time spent in care economy by men and women in unpaid household services and unpaid caregiving services remained almost unchanged. The time spent by women on household chores was around 5 hours across categories of education (Table 4.6). The geographically disaggregated average time (in minutes) spent in a day per participant in different activities reveals that in rural and urban India women spent around 300 minutes on unpaid domestic services for household members as compared to around 98 minutes by men (Table 4.7). In caregiving services for household members, men spent little more than an hour while women spent more than two hours in rural and urban India. The percentage share of total time in different activities in a day per person reveals that in rural India, women spent 17.2 per cent of total time on unpaid domestic services and 2. 6 per cent on unpaid caregiving services for household members; while these figures are, respectively, 1.9 per cent and 0.8 per cent for men (Table 4.8). In urban India, these
SNA production Non-SNA production SNA and non-SNA production Residual other activities All
4.3
23.1
27.3
72.7
100
4
18.4
22.4
77.6
100
2.4
19.4
80.6
100 Urban 17.7
1.9
19.7
80.3
100
Rural
Description of the activity (all India) SNA production Non-SNA production SNA and non-SNA production Residual other activities All
15–59 Years Female
16.9
15–29 Years Male
100
79
21
9.9
11.2
100
76.6
23.4
12.9
10.5
Person
60 Years +
100
72.8
27.2
2.4
24.7
100
74.2
25.8
3.1
22.7
15–29 Years Male
100
72.6
27.4
22.1
5.3
100
68.9
31.1
24
7.2
15–59 Years Female
100
72.7
27.3
12
15.3
100
71.5
28.5
13.6
14.9
Person
60 Years +
100
85.5
14.5
3.3
11.2
100
80.9
19.1
3.6
15.4
15–29 Years Male
100
83.5
16.5
14.2
2.3
100
79.4
20.6
15.1
5.6
15–59 Years Female
Age-disaggregated distribution (%) of time allocation in SNA and Non-SNA, India 2020
Age group
Table 4.4
100
84.5
15.5
8.7
6.8
100
80.2
19.8
9.2
10.7
Person
60 Years +
76 L. S. CHAKRABORTY
25.9
74.1
100
19.5
80.5
100
100
77.3
22.7
11.9
21.7
2.3
Person
60 Years +
10.8
15–59 Years Female
Aggregate 17.2 4.2
15–29 Years Male
100
73.8
26.3
2.8
23.4
15–29 Years Male
100
70
30
23.4
6.6
15–59 Years Female
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
SNA production Non-SNA production SNA and non-SNA production Residual other activities All
Age group
100
71.9
28.1
13.1
15.1
Person
60 Years +
100
82.3
17.7
3.5
14.2
15–29 Years Male
100
80.6
19.4
14.8
4.5
15–59 Years Female
100
81.5
18.5
9
9.4
Person
60 Years + 4 GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
77
157 724
162 737
159 731
404 158 249 113 98 422 145
Person
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
317 123 301 132 98 422 139
434 203 98 77 99 422 151
Employment and related Activities Production of goods for own final use Unpaid domestic services for household members Unpaid caregiving services for household members Unpaid volunteer, trainee and other unpaid work Learning Socializing and communication, community participation and religious practice Culture, leisure, mass-media and sports practices Self-care and maintenance
Female
Male
Rural
171 711
514 134 94 75 111 435 138
Male
Urban
181 720
375 64 293 138 101 425 138
Female
176 715
485 85 247 116 106 430 138
Person
Time allocation of men and women in a day in different activities in India, 2020
Description of the activity (time given in minutes)
Table 4.5
164 729
459 198 97 76 102 426 147
Male
165 723
333 116 299 134 99 423 139
Female
Aggregate
165 726
429 151 248 114 101 424 143
Person
78 L. S. CHAKRABORTY
Employment and related activities Production of goods for own final use Unpaid domestic services for household Unpaid caregiving services for household Unpaid volunteer, trainee and other unpaid
430
196
93
84
87
447
217
108
77
92
Male
94
75
95
197
449
102
73
94
198
464
Not Below Primary Upper Literate primary primary/ middle
Literate and level of education
111
76
95
184
471
Secondary and above
102
76
97
198
459
All
103
126
296
140
342
Female
90
126
301
107
303
98
131
304
108
315
91
131
308
98
305
Not Below Primary Upper Literate primary primary/ middle
Literate and level of education
Time allocation by men and women of different levels of education in India, 2020
Description of the activity
Table 4.6
99
134
299
116
333
All
(continued)
102
146
295
89
349
Secondary and above
4 GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
79
416 125
190
760
366 169
150
751
734
166
438 140
723
156
450 142
710
164
417 149
Secondary and above
729
164
426 147
All
Literate and level of education
738
159
355 159
749
186
411 122
721
165
440 130
713
157
453 131
Not Below Primary Upper Literate primary primary/ middle Female
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
Learning Socializing and communication, community Culture, leisure, mass-media and sports Self-care and maintenance
Literate and level of education
Not Below Primary Upper Literate primary primary/ middle Male
(continued)
Description of the activity
Table 4.6
702
165
410 132
Secondary and above
723
165
423 139
All
80 L. S. CHAKRABORTY
317 123 301 132 98 422 139 157 724
434 203 98 77 99 422 151 162 737
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
Employment and related Activities Production of goods for own final use Unpaid domestic services for household members Unpaid caregiving services for household members Unpaid volunteer, trainee and other unpaid work Learning Socializing and communication, community participation, and religious practice Culture, leisure, mass-media, and sports practices Self-care and maintenance 159 731
404 158 249 113 98 422 145 171 711
514 134 94 75 111 435 138
Male
Person
Male
Female
Urban
Rural
Time allocation in different activities by geography, 2020
Description of the activity
Table 4.7
181 720
375 64 293 138 101 425 138
Female
176 715
485 85 247 116 106 430 138
Person
164 729
459 198 97 76 102 426 147
Male
165 723
333 116 299 134 99 423 139
Female
Aggregate
165 726
429 151 248 114 101 424 143
Person
4 GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
81
4.2 2.2 17.2 2.6 0.1 5.7 8.8 9 50.3 100
16.9 2.7 1.9 0.8 0.2 7.1 9.6 9.7 51.2 100
9.4 50.8 100
10.6 2.4 9.4 1.7 0.1 6.4 9.2
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
Employment and related Activities Production of goods for own final use Unpaid domestic services for household members Unpaid caregiving services for household members Unpaid volunteer, trainee, and other unpaid work Learning Socializing & communication, community participation, and religious practice Culture, leisure, mass-media, and sports practices Self-care and maintenance Total 10.9 49.4 100
21.3 0.3 1.5 0.7 0.2 7 8.7
Male
Person
Urban Female
Rural Male
Distribution (%) of time, by geography and gender, in India, 2020
Description of the activity (all India)
Table 4.8
11.7 50 100
4.3 0.3 16.1 2.5 0.1 6.1 8.8
Female
11.3 49.7 100
13.1 0.3 8.6 1.6 0.1 6.6 8.8
Person
10.1 50.6 100
18.3 1.9 1.7 0.8 0.2 7.1 9.3
9.8 50.2 100
4.2 1.6 16.9 2.6 0.1 5.8 8.8
Female
Aggregate Male
9.9 50.4 100
11.4 1.8 9.2 1.7 0.1 6.5 9
Person
82 L. S. CHAKRABORTY
4
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
83
estimates are 16.9 per cent and 2.6 per cent for women; and 1.7 per cent and 0.8 per cent for men. The percentage of persons participating in different activities as per the usual principal activity status revealed that labour market participation has not reduced the percentage of women participating in unpaid domestic chores in the care economy. Around 93 per cent of women workers (as per broad usual principal status) spent time in unpaid domestic services for household members as compared to 17.8 per cent of men (Table 4.9).
Valuation of Unpaid Care Economy: An Illustration The valuation of the care economy for six selected States in India is attempted, using the estimates of first time-use survey. The first time-use survey found that, in the production of own-account services that qualify for inclusion in the satellite accounts as per SNA 1993, on average, a female spent 34.6 hours per week compared to 3.6 hours by a male (Table 4.10). In these activities, females in Gujarat scored the most time spent (39.08 hours per week), followed by Madhya Pradesh (35.79 hours) and Orissa (35.70 hours). Time-use data of combined states suggest that women spent 50.52 per cent of their time on unpaid work while men spent only 33.15 per cent (Table 4.11). The interstate differences revealed that per cent of time spent by females in unpaid activities was highest in Haryana (85.99 per cent), followed by Meghalaya (76.39 per cent) and Orissa (69.44 per cent); the lowest time spent was in Tamil Nadu (32.45 per cent). Imputing value to labour time spent on unpaid work, the contribution of nonmarket work was estimated across six states of India. Districtwise data on wage rates for agricultural labour and wage rates for urban, unskilled manual labour have been used for valuing unpaid work in rural and urban areas, respectively. With this methodology, projecting the TUS results by age and district of the population, the valuation of time spent on unpaid activities by females in Meghalaya and Madhya Pradesh indicates that the value of unpaid activities could be as much as 38–41 per cent of
84
L. S. CHAKRABORTY
Table 4.9 Percentage of men and women participating in different activities (usual principal activity status) Description of the activity (all India)
Employment and related activities Production of goods for own final use Unpaid domestic services for household members Unpaid caregiving services for household members Unpaid volunteer, trainee, and other unpaid work Learning Socializing and communication, community participation, and religious practice Culture, leisure, mass-media, and sports practices Self-care and maintenance Employment and related activities Production of goods for own final use
Broad usual principal activity status Worker
Unemployed
Labour force
Not in labour force
All
Male 84.9
21.3
82.7
6.3
57.3
18.8
12
18.6
5.6
14.3
31
33.9
31.1
16.1
26.1
17.8
9.7
17.5
7
14
3.2
3.9
3.2
1.6
2.7
1.2 94.4
22.5 96.1
1.9 94.5
67.8 85.2
23.9 91.4
85.2
95.1
85.5
94.6
88.5
100
100
100
100
100
Female 73
12.9
70.9
5.5
18.4
27.9
14.8
27.4
18.2
20
(continued)
4
85
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
Table 4.9 (continued) Description of the activity (all India)
Unpaid domestic services for household members Unpaid caregiving services for household members Unpaid volunteer, trainee and other unpaid work Learning Socializing and communication, community participation, and religious practice Culture, leisure, mass-media and sports practices Self-care and maintenance
Broad usual principal activity status Worker
Unemployed
Labour force
Not in labour force
All
93
85.6
92.8
78.4
81.2
24
18.3
23.8
28.5
27.6
2.8
3.2
2.9
1.8
2
1.7 90.9
34 94.9
2.9 91.1
24 91.3
19.8 91.3
79.9
92.5
80.4
86.5
85.3
100
100
100
100
100
Note (i) The estimates have been calculated considering all the activities in a time slot (ii) Figures may not add up to 100 due to rounding Source Government of India (2020), Time Use Survey 2020, National Statistical Office
the relevant State Domestic Product (SDP). For example, the total value of such activities by females was Rs. 29,034 crore in Madhya Pradesh, relative to SDP of Rs. 70,832 crore (Table 4.12). Compared to females, the valuation of unpaid activities by males was limited to only about 2 per cent of SDP in Gujarat and Haryana. The unpaid work, as a proportion of SDP, is as high as 49.93 per cent in Meghalaya and 47.30 per cent in Madhya Pradesh.
21.26 19.85 17.6 17.07 18.97 26.34 18.72
31.06 35.79 39.08 35.7 30.46 34.52 34.63
115.67 112.38 111.36 115.2 118.61 107.15 114.58
37.7 42.1 43.6 40.1 42.5 45.9 42
SNA
Residual Non-SNA
SNA
Ext- SNA
Male
Female
1.99 4.43 3.19 4.47 3.19 7.16 3.65
Ext-SNA 128.23 121.47 121.12 123.45 122.27 114.78 122.42
Residual Non-SNA
30.19 31.54 31.24 28.69 30.68 35.88 30.75
SNA
Total
15.24 19.22 20.27 19.91 16.87 21.28 18.69
Ext-SNA
Time allocation by women and men, selected states of India (weekly average time in hours)
Haryana Madhya Pradesh Gujarat Orissa Tamil Nadu Meghalaya Combined States
States
Table 4.10
122.52 117.19 116.44 119.36 120.45 110.84 118.62
Residual Non-SNA
86 L. S. CHAKRABORTY
33.09 29.41 44.37 31.25 41.42 17.34 36.54
18.12 23.34 14.17 22.42 13.36 35.39 18.12
35.38 44.25 24.21 41.77 24.39 67.12 33.15
4.13 14.3 17.2 8 21.8 7.83 14.9
Paid
% of time use on unpaid activities
Paid
Unpaid
Female
Male
25.34 15.75 13.87 18.18 10.32 25.34 15.18
Unpaid 85.99 52.4 44.67 69.44 32.45 76.39 50.52
% of time use on unpaid activities
20.6 22.99 33.26 20.55 32.74 12.65 27.16
Paid
Total
Distribution (%) of time use in SNA and Non-SNA: Selected states in India
Haryana Madhya Pradesh Gujarat Orissa Tamil Nadu Meghalaya Combined States
States
Table 4.11
21.37 20.12 14.05 20.47 12.04 30.44 16.85
Unpaid
51.58 46.67 29.7 49.9 26.89 70.64 38.29
% of time use on unpaid activities
4 GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
87
88
L. S. CHAKRABORTY
Table 4.12 Valuation of unpaid care economy: Selected states of India States
Value of nonmarket work (Rs. Crores)
Haryana Madhya Pradesh Gujarat Orissa Tamil Nadu Meghalaya
SDP (Rs. cr.)
“Nonmarket Work” as a % of State Domestic Product
Male
Female
Total
1997–98
Male
Female
Total
928.74 4466.03 2209.55 1463.78 3073.37 260.45
10,209.30 29,034.09 22,577.63 11,343.88 19,922.04 862.97
11,138.04 33,500.12 24,787.18 12,807.65 22,995.40 1123.42
37,427 70,832 86,609 32,669 87,394 2250
2.48 6.31 2.55 4.48 3.52 11.58
27.28 40.99 26.07 34.72 22.8 38.35
29.76 47.3 28.62 39.2 26.31 49.93
Source Pande (2000)
Gender Budgeting: The Link Between Public Investment and Time Allocation The valuation of unpaid care economy has significant policy implications, in terms of gender budgeting. It is often argued that mainstream public expenditure, such as infrastructure, is non-rival in nature and therefore applying a gender lens to these expenditures may not be feasible. This argument is refuted by the time-use statistics. The time-use data revealed that this argument is often flawed, as there is an intrinsic gender dimension to the non-rival expenditure. The time allocation in activities like fetching of water and fuel has significant gender differentials, therefore infrastructure investment with gender-sensitive water and energy policies can really benefit women. The gender-disaggregated statistics of time use in the water sector across the six selected states in India from the first time-use survey clearly revealed that women spent more time in fetching water than men, except in Gujarat (Table 4.13). Apart from the time allocation in the activity, it is to be noted that the travel time for fetching water, fuel, etc. is also equally time-consuming. The time-use data also revealed the gender differentials in travel time. There is thus a clear link between access to water and time allocation of women, who have a primary responsibility to ensure drinking water to their households, which suggests that changes in the availability of water infrastructure can lessen their burden in fetching the water, as well as release their time locked up in nonmarket work for the income-earning economic activities. In other words, investment in water infrastructure
4
89
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
Table 4.13 Time-use pattern by men and women in water sector (weekly average time in hours) States
Haryana Madhya Pradesh Gujarat Orissa Tamil Nadu Meghalaya Combined States
Rural
Urban
Total
Male
Female
Total Male
Female
Total Male
Female Total
3.2 3.21 14 5.96 3.85 4.69 3.83
5.54 5.4 0 8.02 4.79 5.21 5.11
5.38 5.03 14 7.83 4.69 5.04 4.97
4.79 2.96 0 5.21 4.62 7.08 4.63
4.71 2.76 0 5.21 4.26 8.31 4.35
5.48 5.22 0 7.94 4.74 5.34 5.02
3.08 1.21 0 0 2.56 9.54 3.02
3.19 3.11 14 5.96 3.33 5.34 3.61
5.33 4.88 14 7.76 4.57 5.34 4.85
Source Chakraborty (2014)
can help women in reallocating their labour time and reduce the stress related to walking long distances to fetch water. In the next section, an illustrative empirical investigation of this hypothesis is undertaken using the data from the Time-use Survey for variables on time and finance accounts of selected states of India for the variable related to public infrastructure. Ideally, the empirical analysis requires comprehensive time-use data, either in terms of longitudinal surveys or across considerable cross-section units. However, within the data constraints of limited cross-section units of time-use data collected in rural and urban regions of selected states of India, an illustrative analysis is undertaken to examine the link between infrastructure and time allocation. The hypothesis under investigation is whether better access to water infrastructure can help women to spend more time on market-oriented activities. The theoretical framework is given in Box 4.3.
Box 4.3: The link between time allocation and public investment
The link between infrastructure investment and time allocation is interpreted in Becker-Gronau models of time allocation. This framework is derived by refuting the assumption of labor force exogeneity in the treatment of the nonmarket economy, which is intrinsic to the neoclassical labor supply models of consumption and leisure.
90
L. S. CHAKRABORTY
In other words, the model has incorporated the intra-household gender asymmetries in the allocation of time, as well as the choices and constraints regarding labor-force participation in the market and nonmarket economy. The improvised model recognizes the dynamic interaction between the dual sets of economic activity—that is, the statistically invisible nonmarket economy and market economy The model assumes that the household’s utility function depends on the commodities consumed (z i ) and the leisure of its members (ti1 ): u i = u i (z i , t11 , t21 )
(4.1)
Consumption is generated through a household production function: z i = z i (Wi , xi , t1e , t2e )
(4.2)
where W i is the amount of water used by the household, x i is a monetized input, and t i e denotes the time allocated to nonmarket work (e-SNA) by family members; i = 1, 2 The water production function, in turn, is generated by: Wi = f (tiw , Ωi )
(4.3)
where tiw is time allocated to fetch water and parameter Ωi captures the access to water infrastructure The household agents maximize their welfare subject to budget and time constraints given by: max u i = u i (z i , ti1 )
(4.4)
tiw + tim + tie + ti1 ≥ T0
(4.5)
subject to
4
GENDER BUDGETING AND THE EFFICACY OF MEASURING UNPAID …
91
and xi = w1 t1m + w2 t2m + vi
(4.6)
where t1m is the market time, T0 is total time endowment, wi is the market wage rate, and vi is the unearned income Combining Eqs. (4.5) and (4.6), the full income constraint is obtained as follows: (4.7) xi + wi tiw + tie + ti1 = wi T0 + vi Solving for the first order conditions, a set of selected determinants of optimum time and commodity demand functions are derived as follows: t m = t m (w, v, Ω)
(4.8)
x ∗ = x(w, v, Ω)
(4.9)
and
For econometric estimation, a reduced system of time equation is specified as follows: t m = t m (w, v, Ω) + µi
(4.10)
Source Chakraborty (2008).
The model specification is proposed as follows: tim = α + βin f ra i + γ in f rasq i + λti0 + δtic + dummy + u i ; where t i m is time allocation in SNA activity (otherwise referred as market time). The variable infrai denotes allocation and access to water infrastructure. The financial input variable of allocation is proxied by the log of public investment in infrastructure across cross-section units, while access to infrastructure or the distance variable is captured through the timeuse budget of travel (ttimi). The squared term of infrastructure reflects
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the plausible quadratic relationship between access to infrastructure and market time—that is, market time falls with fetching distance but at a decreasing rate. The variable t i o denotes the opportunity cost of time, which is captured through market wage rate. Wage rates for agricultural labour and wage rates for urban, unskilled manual labour have been used for proxying the t i o in rural and urban areas, respectively. The unearned income is proxied by the spouse’s wage in selected models. As variables of opportunity cost of time and unearned income reported multicollinearity problems, estimations are done in separate models. The models are controlled for the nonmonetized work done in the care economy (t i c ). A dummy is defined as takes the value of one if the unit of analysis is rural and a value of zero otherwise. The parameters β and γ measure the effect of infrastructure on time variables; μi is a random error term. The econometric results are given in Table 4.14. Table 4.14 Econometric Link between Infrastructure and Time Allocation Dependent Variable↓
A Log (public infrastraucturei log (public infrastructuresquared)i ttimi (travel time)i
Female Model 2
Model 3
Model 4
149.454 (2.468)* −27.466 (−1.947)* 1.539 −1.859 –
−21.126 (−0.489)
174.714 (4.882)* −18.719 (−2.241)* 1.112 (2.262)* –
101.721 −5.988 –
ttimsqi (travel time squared)i
–
tio (male wage)
–
tio (female wage) tic (non-monetized care economy) Dummy R2 DW
Male
Model 1
0.597 −0.157 −0.588 (−2.298)* 12.699 (7.631)* 0.94 1.85
−1.707 (−0.821) 0.132 −0.579 8.177 −1.024
0.032 −0.072 16.308 (4.669)* 0.91 2.15
–
−12.81 (−4.459)* –
−0.0009 (−0.002) 0.0003 −0.024 −14.056 (−3.673) –
−1.419 (−3.663)* −0.081 (−0.079) 0.88 2.05
−1.363 (−2.601) 0.712 −0.463 0.77 1.95
–
Source (Basic Data), Finance Accounts of selected six States and Time-use Survey (2000)
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The results, though tentative due to data constraints, suggest that there is a quadratic relationship between access to infrastructure and market work; market time decreases with travel time to fetch water, but at a decreasing rate. The estimated coefficients suggest that the relationship between infrastructure access and time allocation in SNA activity is negative, which supports the hypothesis that better public infrastructure may release women’s time to more market-oriented work. The financial input proxy for infrastructure also shows an initially decreasing and then increasing link with SNA activity, which needs a careful interpretation. The results indicate that higher infrastructural investment per se does not release the time of women towards SNA activity. This points to the fact that higher budgetary allocation for infrastructure per se does not mean higher spending. Gender-budgeting studies showed that there is a significant deviation between what is budgeted and what is actually spent (Lahiri et al., 2002). The lag in the implementation of infrastructural projects may be a reason for the concave relationship. The results of linear models are not reported, as the quadratic models turned out to be the better fits. Theoretically, a positive relationship between wages and market work is expected, which explains that as opportunity cost of time rises, women may allocate more time to market work. However, results revealed that wage is not a significant determinant of women’s time in SNA activity. The labour-supply models predict an inverse relationship between unearned income and SNA activity. However, the estimated coefficient of spouse’s wage is not found significant in determining women’s time allocation in SNA activity. The model is controlled for the nonmonetized work in the care economy, inclusive of child care, care for sick, and elderly care. The results showed that there is an inverse relationship between the work in the care economy and market economy, however, it was significant only for the models with financial input variable. Broadly, the estimates suggest that there can be a link between deterioration in infrastructure and rural poverty, as worsening water infrastructure could lock in the time of women in unpaid work that would otherwise be available for income-generating SNA activity. Time poverty affects income poverty; however, the aspects of time poverty are often overlooked when framing macro policies. The point to be noted here is that even with the unit-record data, the analysis of the povertyrelated aspects of time allocation and its implications for public investment may be severely restricted, as time-use data across income quintiles or
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monthly per capita consumer expenditure (mpce) quintiles is not available for India. To conclude, the chapter provides new evidence on the link between public infrastructure and time allocation related to the water sector in India. The estimated coefficients suggest that worsening public infrastructure affects market work with evident gender differentials. The results, though tentative, indicate that access to public infrastructure can lead to substitution effects in time allocation between unpaid work and market work, which has implications for reducing the poverty in the household. In addition to the link between public investment and time allocation, the time-use surveys can also be used to understand the other aspects of macro-fiscal policies including the policies relate to work–life balance, care provider’s perspectives and the dual work burden of women (Amarante & Cecilia, 2018; Antonopolos & Indira, 2004; Arora & Codrina, 2017; Craig & Brendan, 2021; Floro & Hitomi, 2011; ˙ ˙ et al., 2020; Qi & Xiao-yuang, & Emel, 2021; Ilkkaracan Ilkkaracan 2018; Seymour et al., 2020; Stevano et al., 2019). The broad conclusion is that fiscal policies designed to redress income poverty can be partial if they do not take into account aspects of time poverty.
References Amarante, V., & Cecilia, R. (2018). Unfolding patterns of unpaid household work in Latin America. Feminist Economics, 24(1), 1–34. Andrew, A., Sarah, C., Dias, M., Christine, F., Lucy, K., Sonya, K., … Almudena, S. (2020). How are mothers and fathers balancing work and family under lockdown? Institute for Fiscal Studies. Antonopolos, R., & Indira, H. (2004). Unpaid work and the economy gender, time use and poverty in developing countries. Palgrave Macmillan. Arora, D., & Codrina, R. (2017). A gendered model of the peasant household: Time poverty and farm production in rural Mozambique. Feminist Economics, 23(2), 93–119. Bahçe-Kaya, S., & Memi¸s, E. (2013). Estimating the impact of the 2008–09 economic crisis on work time in Turkey. Feminist Economics, 19(3), 181–207. Bardasi, E., & Quentin, W. (2010). Working long hours and having no choice: Time poverty in Guinea. Feminist Economics, 16(3), 45–78. Berik, G., & Ebru, K. (2013). Time allocation of married mothers and fathers in hard times: The 2007–09 US recession. Feminist Economics, 19(3), 208–237. https://doi.org/10.1080/13545701.2013.798425 Bredie, J., & Beeharry, G. (1998). School enrolment decline in Sub-Saharan Africa (World Bank Discussion Paper No. 395).
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Chakraborty, L. (2008). Deficient public infrastructure and private costs: Evidence from a time use survey for the water sector in India (Working Paper No. 536). New York: Levy Economics Institute. Chakraborty, L. (2014). Integrating time in public policy: Empirical description of gender-specific outcomes and budgeting (Working Paper No. 785). Levy Economics Institute (New York: Levy Economics Institute). Chakraborty, L. (2021). Gender analysis of Covid19 economic stimulus packages in Asia Pacific. UN Women. Chakraborty, L., Amandeep, K., Divy, R., & Jannet, F. J. (2021). Covid19 and fiscal-monetary policy responses in Asia Pacific. NIPFP Publications. Craig, L., & Brendan, C. (2021). Working and caring at home: Gender differences in the effects of covid-19 on paid and unpaid labor in Australia. Feminist Economics, 27 (1–2), 310–326. Deshpande, A. (2020). The Covid-19 pandemic and lockdown: First order effects on gender gaps in employment and domestic time use in India. Global Labor Organization, Essen, Germany (Discussion Paper, No. 607). Floro, M. S., & Anant, P. (2010). Gender work intensity and well-being of Thai home-based workers. Feminist Economics, 16(3), 5–44. Floro, M. S., & Hitomi, K. (2011). Gender and work in South Africa: What can time-use data reveal? Feminist Economics, 17 (4), 33–66. Floro, M. S. (1995). Women’s well-being, poverty, and work intensity. Feminist Economics, 1(3), 1–25. Gammage, S. (2010). Time pressed and time poor: Unpaid household work in Guatemala. Feminist Economics, 16(3), 79–112. Government of India. (2020). Time Use Survey 2020. National Statistical Organisation. Gronau, R. (1977). Leisure, home production, and work—The theory of allocation of time revisited. Journal of Political Economy, 85, 1099–1123. Grown, C., Maria, F., & Diane, E. (2010). Unpaid work, time use, poverty and public policy, (Guest Editorial Note). Feminist Economics, 16(3), 5–44. Ilahi, N., & Franque, G. (2000). Public infrastructure and private costs: Water supply and time allocation of women in rural Pakistan. Economic Development and Cultural Change, 49(1), 45–76. ˙ ˙ & Emel, M. (2021). Transformations in the gender gaps in paid Ilkkaracan, I, and unpaid work during the covid-19 pandemic: Findings from Turkey. Feminist Economics, 27 (1–2), 288–309. ˙ ˙ Kijong, K., Masterson, T., Emel, M., & Ajit, Z. (2020). The impact Ilkkaracan, I., of investing in social care on employment generation, time- and income-poverty and gender aps: A macro-micro policy simulation for Turkey. (CWE-GAM Working Paper). Care Work and the Economy-Gender and Macromodeling.
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John, N. A. (2020). Exploring the linkages between women’s paid and unpaid work and their experiences of intimate partner and non-partner violence in Nepal. Feminist Economics, 26(4), 89–113. Juster, F., & Stanford, F. (1985). Time goods and well-being. Institute for Social Research, University of Michigan. Khandker, S. (1988). Determinants of women’s time allocation in rural Bangladesh. Economic Development and Cultural Change, 37 (1), 111–126. Lahiri, A., Chakraborty, L., & Bhattacharyaa, P. N. (2002). Gender budgeting in India, follow the money series. UNIFEM. Motiram, S., & Lars, O. (2010). Gender inequalities in tasks and instruction opportunities within Indian families. Feminist Economics, 16(3), 141–167. Mullan, K. (2010). Valuing parental childcare in the United Kingdom. Feminist Economics, 16(3), 113–139. Pande. (2000). Women’s contribution to economy, project paper on gender budgeting. (Unpublished). National Institute of Public Finance and Policy. Qi, L., & Xiao-yuan, D. (2018). Gender, low-paid status, and time poverty in urban China. Feminist Economics, 24(2), 171–193. Seck, P. A., Encarnacion, J. O., Cecilia, T., & Sara, D.-V. (2021). Gendered impacts of COVID-19 in Asia and the Pacific: Early evidence on deepening socioeconomic inequalities in paid and unpaid work. Feminist Economics, 27 (1–2), 117–132. Seymour, G., Hazel, M., & Agnes, Q. (2020). Measuring time use in developing country agriculture: Evidence from Bangladesh and Uganda. Feminist Economics, 26(3), 169–199. Stevano, S., Suneetha, K., Deborah, J., Malapit, H., Elizabeth, H., & Kalamatianou., S. (2019). Time-use analytics: An improved way of understanding gendered agriculture-nutrition pathways. Feminist Economics, 25(3), 1–22. UNSD. (1993). Systems of national accounts. United Nations Statistical Division. Yamamoto, Y. (2017). Time use and care economy in macroeconomic policy, lecture delivered to UNESCAP officials, in gender and macroeconomic policy training programme. UN Centre.
CHAPTER 5
Determining Gender Equality in Fiscal Federalism: Evidence from India
Fiscal federalism is, inherently, neither good nor bad for gender equality (Chakraborty, 2010a, 2010b; Forster, 2018; Vickers, 2011, 2013). The impact of fiscal federalism on gender-related outcome depends on the interface between institutions and intergovernmental transfer design. Political will, institutional capacity, and commitment towards gender equality are also other significant determinants. Although fiscal federalism is a vast literature, the interface of fiscal federalism with gender equality is scarcely analyzed. Despite the growing recognition of fiscal federalism in gender development in the policy realms, there have been relatively few attempts on the topic. This chapter aims to take on this rare range of significant debate, focusing on the plausibility of incorporating gender into the fiscal transfers. It is particularly relevant in this context that India is the first country to institutionalize gender budgeting within its Ministry of Finance, adhering to the budgetary accounting framework and analyzing the possibilities of changes in the budgetary classification to integrate gender budgeting in the mainstream budgets. To be upfront and brief, amidst the plethora of criteria for fiscal devolution, the right thing to do—even from the gender perspective—appears to be to first make fiscal transfers on a per capita basis, which would be much more even and fiscally equalizing, and then make suitable adjustments for backwardness. It goes without saying that weightage to genuine backwardness, in addition to population, is more redistributive than weightage © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_5
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to population alone. Given the magnitude of missing women in India and the disturbing practices of gender discrimination that exist even before birth, a criterion needs to be incorporated in the unconditional fiscal transfers to penalize the states with an adverse juvenile sex ratio. Amartya Sen set off an impassioned debate when he claimed that millions of women were “missing” in China and India, referring to the number of females who have died as a result of foeticide and unequal access to household resources, nutrition, health care, and access to property rights (Bhalotra et al., 2019; Klasen, 1994, 2008; Klasen & Wink, 2003; Kynch & Sen, 1983). To quote Klasen and Wink (2003) “Missing women refers to the deviation of the actual sex ratio from the expected sex ratio. It is far from a minor issue, but ranks among the worst human catastrophes of the twentieth century as it is larger than the combined casualties of all famines in the twentieth century and it also exceeds the combined death toll of both world wars and the casualties of major epidemics such as the 1918–1920 global influenza epidemic or the currently ongoing AIDS pandemic”. It is critical to assess the role of public policy, within fiscal federalism, in addressing gender inequality (Chakraborty, 2010b). The nature of gender-related concerns varies across this very diverse region, and ranges from a focus on addressing the burden of the unpaid care economy to redressing female deprivation in education and health. Gender budgeting is ideally an approach to fiscal policies and administration that translates gender commitments into fiscal commitments through identified processes, resources, and institutional mechanisms, and can work on both the spending and revenue sides of the budget.
Theoretical and Empirical Literature The theoretical literature on intergovernmental transfers largely deals with the conceptual elements and design of intergovernmental fiscal transfers (IGFT) in a context of competitive federalism (Boadway & Shah, 2007; Bird & Smart, 2002; De Mello, 2000; Hinojosa et al., 2010; Musgrave, 1997; Smart, 1996). The relative effectiveness of intergovernmental transfers on fiscal spending—flypaper effects—is analyzed but without a gender perspective (Stotsky et al., 2019). Habibi et al. (2003) in the context of Argentina analyze the impact of fiscal transfers on human development and found a positive relationship between the two. Lü (2011) analyses the effect of intergovernmental fiscal transfers on education spending
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in the context of China for the period 1994–2000 and could not find strong effects. Litschig and Morrison (2013) analyze the link between fiscal transfers and local public expenditure in Brazil for the education sector. Their results reveal that there is a positive and significant relationship between transfers and local education spending, and between per capita spending and education outcomes. In India, Chakraborty L. (2016a, 2016b, 2020a, 2020b, 2020c, 2021), Chakraborty and Chakraborty (2016), Chakraborty P. (2021), Isaac and Chakraborty (2008), Rao (2018), and Rao and Singh (2007) examine fiscal federal relations and the subnational state finances in the context of India. Only a few of the existing studies on IGFT in India have incorporated gender equity concerns. Chakraborty (2010a, 2010b) and Anand and Chakraborty (2016) examine how integrating gender criteria/principles in the IGFT formula can improve horizontal equalization across jurisdictions. Chakraborty et al. (2018) look at how conditional transfers can alter gender equality outcomes. Within the intergovernmental transfer framework, the impact of gender budgeting on gender outcomes is a new area of empirical research. Stotsky and Zaman (2016) analyze the impact of gender budgeting on gender equality outcomes in the context of India and found that gender budgeting has a positive effect on gender equality in education at the primary and secondary levels. Chakraborty et al. (2017) analyze the effectiveness of gender budgeting on sectoral gender outcomes in the context of the Asia Pacific region. They find that gender budgeting has a positive and significant effect on education and health outcomes, but there is no impact on labour force participation rates. This reinforces the view that care economy policies to augur the female work force participation have been meagre in the region. One shortcoming of this existing research on the gender budgeting research in the Indian context is that this study does not incorporate IGFT on gender equality outcomes. The integration of IGFT into a model examining the determinants of gender equality outcomes and fiscal spending, controlling for gender budgeting, is the main innovation here and provides a more realistic view of subnational decision-making in India. In addition, the feminization of governance at the third tier could change the types of public expenditure at the local level to correspond more to the revealed preferences (“voice”) by women. An MIT study by Raghabendra Chattopadhyay and Esther Duflo (2001) has measured the impact of the feminization of governance at the local level on the
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outcomes of decentralization with data collected from a survey of all investments in local public goods made by the village councils in one district in West Bengal. They found that women leaders of village councils invest more in infrastructure that is relevant to the needs of rural women (like drinking water, fuel, and roads) and that village women are more likely to participate in the policymaking process if the leader of their village council is a woman. Thus, placing women in a leadership position in governance at the local level can change the expenditure decisions of the local bodies and, in turn, change the types of public-good investments at the local level to correspond more to the revealed preferences (voice) by women (Stern, 2002). The study, however, has confronted a few criticisms. Bardhan and Mookherjee (2000) noted that without direct evidence on the nature of women’s preferences relative to men’s, and since women’s reservation in the leadership positions in local government was not linked to the distribution of women in the village, this study does not quite address how local democracy affects the underrepresented groups in the village to implement their desired outcomes. There is a growing recognition that fiscal policy can redress intrahousehold inequalities in terms of household division of labour by supporting initiatives that reduce the time allocation of women in unpaid work. Examples of such government intervention are improved infrastructure in water sector, rural electrification, sanitation services, and better transport infrastructure. As analyzed in Chapter 4, the public infrastructure deficit in rural areas may deepen rural poverty due to the time allocation across gender skewed towards more unpaid work, which is time otherwise available for income-earning market economy activities. Public investment in infrastructure, like water and fuel, can also have positive social externalities in terms of educating the girl child and improving the health and nutritional aspects of the household. There can be a link between deterioration in infrastructure and rural poverty. In terms of fiscal policies to redress poverty, the aspects of time poverty are often surpassed. Time poverty affects income poverty. Fiscal policies designed to redress income poverty can be partial if they do not take into account the aspects of time poverty. This policy discussion has gender dimension, as women are time poor and fiscal policies designed for pro-poor measures need to incorporate the time allocation aspects across gender. Using time-use statistics of water revealed that the incidence is significantly higher for girls and women in both rural and urban areas, which, in turn, points to the deficiency in adequate infrastructure in water and
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sanitation (Chakraborty, 2008, 2009). It has significant fiscal policy implications, as easy accessibility to drinking water facilities might lead to an increase in school enrolment, particularly for girls, by reducing the time utilized for fetching water. In other words, time budget statistics enable the identification of the complementary fiscal services required for better gender-sensitive human development.
Fiscal Federalism in India: Institutional Details There is a growing recognition that something fundamental is happening in Indian fiscal federalism ex post institutional changes such as the abolition of the Planning Commission, the creation of the National Institution for Transforming India (NITI) Aayog, the constitutional amendment to introduce the Goods and Services Tax (GST), the establishment of the GST Council, and the historically high tax devolution to the states based on the 14th Finance Commission’s recommendations. Recently, policymakers and experts have raised a few issues, including: whether or not to make Finance Commissions “permanent” or to abolish them by making the tax devolution share constant through a constitutional amendment; the need for an institution to redress spatial inequalities in order to fill the vacuum created by abolishing the Planning Commission; and making the case for Article 282 of the constitution to be circumscribed. The debates are also focused on whether there is a need to establish a link between the GST Council and Finance Commissions, and if India should devise a mechanism of transfer that is predominantly based on sharing of grants for equalization of services rather than tax sharing. Creating a plausible framework for debt-deficit dynamics while keeping the fiscal autonomy of states intact and ensuring output gap reduction and public investment at the subnational level without creating disequilibrium were also other matters of concern. These debates are significant, especially when a group of states came together for the first time ever to question the terms of reference of the 15th Finance Commission amid growing tensions in the federal-state relations in India. The historically high 42 per cent devolution of the central government’s divisible tax pool to the states, as recommended by the 14th FC, was hailed by governments and scholars in India and abroad alike. The same magnitude is retained in the Fifteenth Finance Commission. However, if we look at the aggregate transfers to the states as a percentage of gross revenue of the central government, it has remained constant
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over the years (Chakraborty, P., 2021). A concern whether the labyrinth of “entitlement-based central legislations” (for instance, the Mahatma Gandhi National Rural Employment Guarantee Act of 2005, the Right of Children to Free and Compulsory Education Act of 2009, and the National Food Security Act of 2013) conflict with the 7th schedule of the constitution (based on Article 246) was one of the highlights of the contemporary federalism debates (Singh, 2019). The 7th schedule of the constitution clearly lays down the subjects for the union list (expenditure functions assigned to the federal government), the concurrent list (shared functions between federal and state governments), and the state list (functions exclusively assigned to the state governments), with the expectation that each will respect the territorial limits of the other. Over the years, there has been a transgression of the central government into state subjects through centrally sponsored schemes (CSS) and the enlargement of the concurrent list (Reddy & Reddy, 2019, 76) on the grounds that such spending will better serve national priorities. It was cautioned that through this process, the fiscal autonomy of the Indian states was severely circumscribed. This intergovernmental fiscal transfer (IGFT) outside the purview of the Finance Commissions is the most sensitive part of the federal-state fiscal relations in India, as the states feel that these transfers are large, discretionary, arbitrary, and regressive (Reddy & Reddy, 2019, 77). Have things changed after the 14th FC award? The answer is mixed. The share of general-purpose transfers that are unconditional has increased from 51.41 per cent of the total to around 60 per cent of the total, with a corresponding decline in specific-purpose or conditional transfers (Chakraborty et al., 2018). Article 282 of the constitution says: “The Union or a State may make any grants for any public purpose, notwithstanding that the purpose is not one with respect to which Parliament or the Legislature of the State, as the case may be, may make laws”. Though Article 282 embodies merely a residuary power, it has been misused totally outside the frames of constitution. How to resolve this contradiction, which creates a dichotomy in the functions of the FCs, requires wider debate (Singh, 2019). With the 42 per cent tax devolution and the rationalization of CSS—mostly conditional grants—prior to the abolition of the Planning Commission, there is a “triumph of experience over expectations” (Reddy & Reddy, 2019, p. 74). The need for an institutional mechanism, such as a “fiscal council”, to enforce fiscal rules and keep a check on the central government’s fiscal
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consolidation was highlighted. Singh (2019) emphasized that there is a need for a consolidated fiscal roadmap for both the central government and the states, with the same rules of the game for both. Another concern is that there is no constitutional check over borrowings for the central government, only for state government liabilities, as Article 293 (3) provides a constitutional check over state borrowings. Is there a need for an institution to redress spatial inequalities in order to fill the vacuum created by abolishing the Planning Commission? One aspect that did not receive adequate recognition in the context of “what holds India together” is the role of the Finance Commissions. Reddy and Reddy (2019) rightly highlights the significance of the existing institutional mechanisms, such as a Finance Commission, for providing “predictability in the federal fiscal relations”, along with a smooth transition of political regimes through peaceful elections, state reorganization mechanisms, and the other institutions of economic management. Reddy and Reddy (2019) sheds light on these aspects of “asymmetric” and “cooperative” federalism in India. The effectiveness of fiscal federalism in creating “convergence” is an empirical question and such empirical questions have gained significance globally. In India, has the “equality of processes” in fiscal federalism resulted inequality of outcomes? Has this goal of economic convergence been achieved, with poor states catching up in growth with the richer Indian states? Existing empirical evidence is mixed. There is convergence in social sector outcomes, such as in education and health, but there is no economic convergence. Reddy and Reddy (2019) has effectively analyzed how the formation of states, economic convergence, and efficiency-equity principles have intertemporally influenced the thought processes of various Finance Commissions. One such crucial empirical question is about an economy’s reliance on history. When the global recession gripped the schools of thought in economics, macroeconomists started realizing financial economics’ reliance on history. However, we still do not well understand the significance of the impact of this hysteresis on macroeconomic stability, growth, and development in the evolution of fiscal federal design. There is a debate about the significance of conditional versus unconditional fiscal transfers. Some economists believe in a quick economic rebound to global goals and economic convergence through designing a plethora of conditional transfers, while some others raise concerns over transfers that are broadly of a one-size-fits-all design. Reddy and Reddy (2019) highlighted the lack of capacity to implement such one-size-fits-all
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transfers and suggested unconditionality in fiscal transfers. They highlight these questions and remain stoic about them, leaving a cue that researchers need to examine them empirically through the progressivity analysis of tax transfers versus grants. On public debt, it is contextual to recall the extensive recourse to seigniorage financing—the automatic monetization—since 1957 by providing net RBI credit to the government to finance deficits, and the subsequent shift in the financing pattern from money financing to bond financing since 1990s after to the economic reforms. At the state level, fiscal rules determine a state’s access to debt, subject to the approval of the central government. It is interesting to recall the changing perceptions on public debt in macroeconomic debates globally. The recent Fiscal Responsibility and Budget Management/rule-based fiscal policy in India stipulates a 60 per cent threshold for public debt as part of fiscal consolidation. An empirical question one could pose here is whether a state’s access to public debt, though not good, can be so bad? Of course the answer is: It is context specific. So what could be the plausible analytical framework to be considered when a Finance Commission takes steps towards public debt management? Oliver Blanchard at the American Economic Association (AEA) meetings in Atlanta in January 2019 had put it up front that “public debt has no fiscal costs if the real rate of interest is not greater than the real rate of growth of the economy” (Blanchard, 2019). He also highlighted that high public debt is not catastrophic if more debt can be justified by clear benefits, like public investment or output gap reduction. He also highlighted the hysteresis effects (the persistent impact of short-run fluctuations on the long-term potential output) and suggested that a temporary fiscal expansion during a contraction could reduce debt over a longer horizon. There is an increasing recognition of the fact that public investment has suffered from fiscal consolidation across advanced and emerging economies (Blanchard, 2019). This is particularly important when public investment is one of the crucial determinants in strengthening private corporate investment in the context of emerging economies (Chakraborty, 2016a, 2016b; Vinod et al., 2020). Blanchard (2019) mentioned that if we are worried about a bad equilibrium, it is better to have a contingent fiscal rule (which may not need to be used) rather than steady fiscal consolidation. Similarly, Reddy and Reddy (2019) noted that a uniform and rigid fiscal rule not only undermines the fiscal autonomy of the states, but would also result in public (developmental) expenditure compression
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to comply with the numerical thresholds. This is refreshing, especially in the context when the path towards fiscal consolidation is equally important as the debt-target thresholds, because fiscal consolidation through strengthening tax buoyancy rather than public expenditure compression can be less detrimental to economic growth. However the output gap can be a difficult notion for Finance Commissions. Extreme precaution is required when we measure deficits. It may be incorrect to think that cyclically adjusted fiscal deficit instead of fiscal deficit is what the Finance Commissions need to focus on. The empirical literature notes that we do not know whether disruptions or downturns permanently depress the level of output and employment or whether the economy can bounce back to its initial upward trend after a decline (as in the notion of a business cycle). In emerging economies there could be a drop from the trend growth rather than a deviation from the trend, illustrating that the “cycle is the trend” (Aguiar & Gopinath, 2007). The cyclicality of deficits can be challenging, as they cannot assume that an upturn in the business cycle can eliminate the cyclical part of a deficit. Such elimination cannot happen if the economic growth cycle does not return to its prior trend growth path and therefore the buoyancy of revenue receipts could remain below their prior potential level. Reddy and Reddy (2019) gives importance to fiscal decentralization. When it comes to the local government (the third tier), the real issue is unfunded mandates. To analyze this empirically, we need reliable data for the third tier. In India, general government data is a challenge. IMF government finance statistics give cross-country data on the general government (inclusive of national, state, and local governments). The role of the State Finance Commissions (SFCs) also needs to be emphasized given their significance in providing a steady flow of funds to the local governments. There is an increasing concern about the arbitrariness and ad-hocism of fiscal transfers at the third tier. The cross-country experiences of federalism, realizing how different Indian fiscal federalism is from other countries’ models. In other federations, IGFTs are predominantly grants, not tax transfers, so such fiscal equalization models may be of different relevance to India.
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Fiscal Federalism Arrangements and Gender Equality In India, the Finance Commission, erstwhile Planning Commission and line ministries of the Union government are responsible for IGFT. India has had 15 Finance Commissions since independence. The duties mandated for the Finance Commission are as follows: (a) the distribution between the Union and the States of the net proceeds of taxes which are to be, or maybe, divided between them and the allocation between the States of the respective shares of such proceeds; (b) the principles which should govern the grants in aid of the revenues of the States out of the Consolidated Fund of India; and (c) any other matter referred to the Commission by the President in the interests of sound finance. The Finance Commission’s recommendations in India are so far conclusively accepted by the National Parliament. After the Parliament accepts the recommendations, the Finance Commission awards to the states, as per their formula, becomes mandatory and these transfers are also therefore referred to as “statutory fiscal transfers”. These statutory transfers are unconditional grants or “general purpose transfers”. Until recently, a substantial flow of transfers in the form of intergovernmental “grants” has been transferred through the erstwhile Planning Commission of India. The Planning Commission was abolished in 2014. In place of the Planning Commission, the National Institute for Transforming India (NITI) Aayog has been constituted as a think tank to foster cooperative federalism in the country, with no role for intergovernmental fiscal transfers to the states of India. The non-statutory transfers are channelled through the line ministries mostly as conditional grants or tied grants for specific purposes. These conditional grants are also referred to as “centrally sponsored schemes”. Ensuring gender equality in fiscal policies, not only helps to access equitable share of benefits and costs across gender, but also helps in ensuring equity in empowering them. Strengthening of “agency” in women helps in providing greater opportunities and access to paid work, enhances productivity and economically empowers women. Empowerment improves entitlements and thus, enhances economic, social, and
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political status of the disadvantaged and gives them a greater role in the design most important way in which this can be accomplished is through ensuring gender equity in human development. Anand and Chakraborty (2018) showed that integrating a gender variable as one of the criteria for intergovernmental fiscal transfers has four advantages. One, it incentivizes states to improve gender inequality. Two, it makes the fund transfer more progressive, Three, it also benefits the poorer states, as the correlation between the gender inequalities and poverty is high. Finally, it makes the per capita income across states, post devolution, more equitable, and increases progressivity in the intergovernmental fiscal transfers. While social values and ethics reflected in the demographic performance of a state cannot be changed by fiscal fiats alone, a proactive approach by a high constitutional body like the Finance Commission (FC) has always been called for (Chakraborty, 2020a, 2020b, 2020c). This is especially when these prejudices—reflected in the demographic patterns—are blatantly oppressive. For instance, 15th Finance Commission’s decision to give 12.5 per cent weightage to “demographic performance” is laudable. The Commission has decided to use total fertility rate (TFR)—instead of other plausible indicators like the female population of the states or the sex ratio of 0–6 age group—as an indicator of “demographic performance”. It was noted that the reduction of TFR—the average number of children that would be born to a woman over her lifetime—also reflects better performance in maternal and child health as well as education, and it reflects the quality of human capital. Given the disturbing demographics, there has been a growing recognition over the years to the plausibility of incorporating gender into tax transfer formula in India. With the monotonous decline in the 0–6 sex ratio in India, it was believed that there can be no valid objection to using FC transfers for gender equity. Chakraborty (2010a, 2010b) suggested was to use a simple method for introducing some weight in favour of the female population of the states in the fiscal devolution formula. Chakraborty (2020a, 2020b, 2020c) argued that the message would be even stronger and more appropriate if the number of girls in the 0–6 age cohort—is adopted as the basis for determining the states’ relative shares of the amount to be disbursed by applying the allotted weight. The demographic pattern of 0–6 age group can also capture the
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gender discrimination “even before birth”. It remains an empirical question whether incorporating TFR or a sex ratio (0–6) makes FC transfers more progressive/equitable (Anand & Chakraborty, 2016). This progressivity analysis is significant to know whether TFR is a better criterion than the other in capturing the “demographic performance”. In addition to incorporating gender criteria in tax transfer formula, specific-purpose transfers can also strengthen the gender budgeting initiatives at the subnational levels, including the third tier. For instance, in India, with the advent of fiscal decentralization aftermath 73rd and 74th Constitutional Amendments and the feminization of local governance in India (33 per cent reservation for women), the imperative for gender equity will be even stronger if the specific-purpose transfers can facilitate integrating the revealed preferences (“voice”) of women in local level public expenditure decisions. Ethiopia, too, is in the process of integrating gender in IGFT. In Ethiopia, the process has been initiated by the House of Federations (Senate) and the Terms of Reference (TOR) was moved in Parliament for public hearing. Subsequently, a majority was secured in the Senate for gender-integrated TOR and the country is waiting for the “proclamation” by the Senate to make it a reality in their forthcoming Fiscal Commission. NIPFP has worked in close association with the House of Federation (Senate), the Government of Ethiopia, and the Forum of Federation in this process of integrating gender in fiscal transfers in Ethiopia (Chakraborty, 2020a, 2020b, 2020c).
The Empirical Models and Results The data are obtained from the IMF Database on gender created in 2016, as part of IMF initiative on gender budgeting, the State Finance Accounts (for budgeted unconditional transfers), federal government ministry web sites (for budgeted conditional transfers), and the Ministry of Women and Child Development (MWCD) gender budgeting information. The descriptive statistics of the variables are given in Table 5.1. The data cover the period 1991–2015. During this period, 16 of the states adopted gender budgeting and 13 did not. We do not include Union Territories because they have limited fiscal autonomy. The effects of intergovernmental transfers on gender outcomes across the states of India, controlling for whether states have gender budgeting initiatives in place, is analyzed (first model). The flypaper effects, whether fiscal transfers have more impact on subnational spending than own
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Table 5.1 Descriptive statistics Variable (all log terms unless otherwise noted)
N
Real per capita income (in millions) Real per capita income Population Real per capita aggregate transfer Real per capita unconditional transfers Real per capita conditional transfers Real per capita Total public expenditure Real per capita education expenditure Real per capita health expenditure Real per capita infrastructure expenditure Real per capita own revenue
364
Mean 64,713.8
Median
Std. Dev
56,485.64 37,163.6
Min 13,025.8
Max 257,354
364 364 364
10.94 2.78 6.21
10.94 0.53 3.33 1.62 5.97 1
9.47 12.46 −0.6 5.35 4.05 8.47
364
5.28
5.32 0.65
3.54 7.12
364
5.5
4.99 1.34
3.13 8.25
364
9.51
9.45 0.68
8.04 11.36
364
7.66
7.6
0.62
6.38 9.44
364
6.36
6.25 0.73
4.85 8.33
364
7.49
7.37 0.81
5.68 9.84
364
6.1
6.04 0.83
4.06 8.47
Sources IMF database, Finance Accounts of state governments, and federal government ministry websites, as in Stotsky et al. (2019)
revenues, is also tested (second model). Prima facie, we assume that if the impact of intergovernmental fiscal transfers is significantly more than that of own revenue, there is a flypaper effect. The flypaper effects of ecological fiscal transfers are attempted in the context of India and found a significant link (Chakraborty, 2021; Kaur et al., 2021). Gender budgeting initiatives are difficult to quantify (Stotsky et al., 2019). The specifically targeted allocations for gender development are broadly less than one percent of the entire budget and that is not the entire spending on gender equality. The remaining 99 per cent of the budget often has intrinsic gender-related objectives. Unless we try to quantify this spending as well, using the specifically targeted public spending on gender equality represents only a partial measure. The public spending on gender as a proxy for gender budgeting initiatives is avoided for this reason.
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Another dimension of effectiveness of gender budgeting in any state is whether it is made mandatory through legal procedures or not. However, in India (unlike in some countries or subnational entities, where gender budgeting is mandatory), gender budgeting was not made mandatory through law (Stotsky et al., 2019). A third dimension is to categorize the states as per the phase of gender budgeting—whether a state is in an early phase of model building, or second phase of developing gender budgeting statements using matrices and institutionalizing it in the Finance Ministry, or third phase of capacity building of sectoral ministries in integrating gender budgeting and/or in a final phase of designing accountability mechanisms of gender budgeting to understand its impacts (Chakraborty et al., 2021). These four phases are unclear in the state context and therefore an attempt to establish in which phase the different states were, as a measure of gender budgeting in our econometric models, is not undertaken (Stotsky et al., 2019). Given the data limitations, following Stotsky and Zaman (2016), the states are categorized into gender budgeting and non-gender budgeting states based on the announcement by the government to initiate gender budgeting in any state. We measure the effect of gender budgeting through the use of a dummy variable, where the variable takes a value of 1, if the state has a gender budgeting effort in place and 0, if the state does not. The gender budgeting regime dummies are also matched to the year of implementation of gender budgeting. The year of implementation is used as a regime changing dummy because gender budgeting has not been rolled back in any of the states of India where it has been initiated (Stotsky et al., 2019). Stotsky et al. (2019) estimate the following equations to measure the impact of intergovernmental fiscal transfers and gender budgeting on gender equality outcomes and the fiscal stance respectively. Gender Inequalityit = β1 Gender Budgetingit + β2 Fiscal Transfersit + δXit + ηi + νt + εit State Public Expenditureit = β1 Gender Budgetingit + β2 Fiscal Transfersit + β3 Own Revenueit + δXit + ηi + νt + εit The social and cultural variables like religion are excluded in the models because the unit of analysis is the Indian States in which religion is
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non-homogenous. The fiscal transfers are included not as direct benefit transfers (DBT) to households or individuals, but intergovernmental fiscal transfers from higher government to subnational governments (Stotsky et al., 2019). The political economy variables are not included in the model because intergovernmental fiscal transfers are broadly based on formula or criteria (including population, per capita income, climate change related variables, fiscal discipline), and the discretionary elements arising from political affiliation of national and subnational governments do not appear to be significant variables in determining the IGFT mechanism in India (Stotsky et al., 2019). The ethno-fragmentation of the population of the subnational governments in deciding the quantum of transfers is also beyond the scope of the study, for the same reasons. As noted in Stotsky and Zaman (2016), ideally, the other variables for gender inequality in education beyond the gender parity in enrolment index. However, the database unfortunately does not provide any other gender outcome variables for states of India across time in education. Stotsky et al. (2019) use the following variables as determinants: real income per capita and per capita intergovernmental transfers from the Union government, which is disaggregated in the models into conditional and unconditional fiscal transfers, both measured in the natural log of real per capita amounts; population, measured in millions; and agriculture GDP, manufacturing GDP, and services GDP, all measured as a ratio of subnational GDP. Population is used to control for economies of scale in provision of public services and might also have an effect of gender inequality through indirect means (for instance, states with larger populations might be more exposed to outside influences) (Stotsky & Zaman, 2016). The structural transformation of the economy is captured through the share of the state economy in various types of economic activity. This can affect gender equality outcomes by influencing how women participate in economic activity. In India, “participation income” (income received by participating in economic activity) is more consequential than universal “basic income” (the income transferred to individuals through public policies, irrespective of their participation in economic activity). Public spending on health and education can reflect the revealed preferences of the state incorporating the median voter’s utilities (assuming that there is a “Wicksellian connection”, meaning there is a link between one unit of tax paid and one unit of utils derived by citizens).
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The generalized method of moments (GMM) approaches—using the Arellano and Bond methodology—is used to account for a lagged dependent variable and to address the potential endogeneity of the independent variables. The lagged dependent variable captured in the GMM models can better measure the dynamic process by which gender equality indicators and spending measures evolve over time. The unconditional transfers have a positive and significant effect on gender parity in education in the upper secondary levels. Gender budgeting has a positive and significant impact on gender parity in education at the upper primary school and lower secondary school levels. The conditional transfers are not significant (Table 5.2). The results also suggest that economic growth per se is insufficient, given the weak impact of real income changes, and therefore that the government needs to take specific and focused public policy planning and budgeting measures to ensure gender equality outcomes in India. The second part of the empirical work examines the effect of IGFT, own revenues, and gender budgeting on fiscal spending. We also examine flypaper effects—whether money sticks where it hits or whether the impact of IGFT is more than own revenue on fiscal spending at the subnational levels. In this analysis, the dependent variable is the log per capita fiscal spending variables. The independent variables are the same as before. Table 5.3 presents results for the GMM estimations of flypaper effects. The own revenue per capita is found to have a significant positive effect on fiscal spending, except in the education sector. The conditional IGFT is positive and significant in determining state infrastructure spending. The unconditional IGFT is not significant in determining state spending, except for a negative impact in the health sector (Stotsky et al., 2019). The IGFT has “substitution effects” with subnational public spending only in the health sector. Gender budgeting has a significant impact on spending at the aggregate level, and only in the education sector. Income is significant, except in health. These results show some variation with the fixed effects. The most consistent finding is the positive effect of gender budgeting on education spending, consistent with the earlier findings of a positive effect of gender budgeting on enrolment parity. Overall, these results suggest that conditional fiscal transfers and gender budgeting exert some positive effect on fiscal spending. These empirical findings are consistent with the underlying policy formulations
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Table 5.2 Impact of intergovernmental fiscal transfers on gender equality, with lagged gender budgeting dependent variable: GMM estimates Variables
Gender equality index lower primary school (female to male ratio)
Gender equality index upper primary school (female to male ratio)
Gender equality index lower secondary school (female to male ratio)
Gender equality index upper secondary school (female to male ratio)
L1
−0.2722 (0.122) 0.0157 (0.0150)
0.3058* (0.137) 0.005 (0.0176)
−0.297* (0.257) 0.074 (0.047)
−0.258 (0.0217) 0.127** (0.041)
0.0088 (0.1156)
−0.0079 (0.0140)
−0.037 (0.035)
−0.012 (0.033)
0.0029 (0.0225)
0.0609** (0.0275)
0.1996 (0.1217)
−0.0133 (0.098)
0.074 (0.057) −0.305 (0.475)
0.0675 (0.067) 0.2602 (0.558)
0.622 (0.442) 0.370 (1.011)
1.211** (0.515) 0.304 (0.992)
−0.306 (0.475)
0.2588 (0.558)
0.369 (1.011)
0.304 (0.992)
−0.306 (0.475)
0.2598 (0.5579)
0.374 (1.012)
0.303 (0.992)
0.009 (0.102) 30.92 (47.51)
0.0218** (0.012) −26.148 (55.78)
0.0399** (0.0206) −38.65 (101.14)
0.028 (0.0198) −33.09 (99.22)
Real per capita unconditional transfers (log terms) Real per capita conditional transfers (log terms) Real income per capita (log terms) Population (log terms) Agriculture GSDP (% of State GSDP) Manuf. GSDP (% of State GSDP) Services GSDP (% of State GSDP) Gender budgeting Constant
* 1 % level of significance Sources IMF database, Finance Accounts of state governments, and federal government ministry websites, as in Stotsky et al. (2019)
of tied central transfers with a matching component of fiscal spending by the subnational governments. To conclude, using panel estimations, we found that unconditional transfers have a significant and positive impact on gender parity outcomes, measured as enrolment parity, in the education sector at primary
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Table 5.3 Impact of IGFT and gender budgeting on fiscal spending, with lagged de-pendent variable—GMM estimates Variables
Total public expenditure
Education expenditure
Health expenditure
Infrastructure expenditure
L1
0.129* (0.056) 0.242*** (0.034)
0.486*** (0.055) −0.015 (0.049)
0.575*** (0.0628) 0.1639* (0.064)
0.364*** (0.062) 0.167** (0.022)
−0.036 (0.036)
−0.0601 (0.046)
−0.168** (0.064)
0.0436 (0.068)
0.0297 (0.024)
−0.036 (0.0328)
0.001 (0.047)
0.144** (0.055)
0.0296** (0.0286) 0.691*** (0.724) −0.087 (0.185) 0.236 (1.296) 0.235 (1.296) 0.241 (1.296) −26.63 (129.59)
−0.065 (0.042) 0.594 (0.101) −0.208 (0.240) 1.174 (1.799) 1.174 (1.799) 1.174 (1.799) −120.699 (179.87)
−0.023 (0.0472) 0.393*** (0.111) −1.247*** (0.238) 1.119 (1.956) 1.122 (1.955) 1.126 (1.955) −110.448 (195.548)
Real per capita own revenue (log terms) Real per capita unconditional transfers (log terms) Real per capita conditional transfers (log terms) Gender budgeting
0.0578** (0.0219) 0.5859*** Real per capita income (log terms) (0.053) 0.045 Population (log (0.124) terms) Agriculture GSDP 1.001 (% of State GSDP) (0.944) 0.995 Industries GSDP (% of State GSDP) (0.944) Services GSDP (% 1.006 (0.944) of State GSDP) Constant −99.978 (94.43)
* 1 % level of significance Sources IMF database, Finance Accounts of state governments, and federal government ministry websites, as in Stotsky et al. (2019)
and secondary levels, in comparison to conditional transfers. Gender budgeting is an effective policy tool for promoting gender equality outcomes in education at the state level. Fiscal spending is influenced both by own revenue and IGFT. Own revenue exerts a positive and significant effect on spending, as theory would suggest. Conditional or tied transfers also have a positive effect, in some models. This result likely reflects the design of tied transfers in India within a “co-operative federalism” framework. States must provide a matching component to a tied
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grant from the Union government in certain sectors. Unconditional fiscal transfers are generally found ineffective in determining fiscal spending, an interesting finding, because these transfers should function like own revenues. This result may reflect a discrepancy between budgeted and actual spending, which requires more detailed data investigation. As an exception, however, in the health sector, a “substitution effect” is noted in the GMM model, meaning fiscal transfers in health are negatively related to state-level public spending on health. Gender budgeting as a policy tool is found to have mixed effects in determining state-level fiscal spending at aggregate and disaggregate sectoral levels. The unconditional fiscal transfers seem to have a direct effect on gender equality outcomes measured by parity in enrolment compared to conditional transfers and therefore integrating gender criteria in intergovernmental formula-linked fiscal devolution would have positive effects on gender equality, even though the exact mechanism is unclear. Income gains are not sufficient to generate equality of outcomes. Gender budgeting has also been found to have been useful in promoting gender equality. However, given the exact mechanism of influence, further investigation with more detailed fiscal and demographic data and at a finer level for transfer programs is called for.
References Aguiar, M., & Gopinath, G. (2007). Emerging market business cycles: The cycle is the trend. Journal of Political Economy, 115, 69–102. Anand, A., & Chakraborty, L. (2016). Engendering’ intergovernmental transfers: Is there a case for gender-sensitive horizontal fiscal equalization? (Working Paper 874). The Levy Economics Institute of Bard College. Bardhan, P., & Dilip, M. (2000). Decentralizing anti-poverty program delivery in developing countries (Working Paper C98-104.1). Center for International and Development Economics Research (CIDER), University of California. Bhalotra, S., Abhishek, C., Dilip, M., & Francisco, J. P. (2019). Property rights and gender bias: Evidence from land reform in West Bengal. American Economic Journal: Applied Economics, 11, 205–237. Bird, R., & Smart, M. (2002). Intergovernmental fiscal transfers: International lessons for developing countries. World Development, 30(6). Blanchard, O. (2019). Public debt and low interest rate. Presidential address, delivered at the American Economic Association Meetings, Atlanta (January 6).
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Boadway, R., & Shah, A. (2007). Intergovernmental fiscal transfers: Principles and practice public sector governance and accountability (Working Paper Series). The World Bank. Chakraborty, L. (2008). Analysis of Kerala state budget 2007–08 through a gender lens. Centre for Development Studies. Chakraborty, L. (2009). Fiscal decentralization and gender budgeting in Mexico: An empirical analysis. Regional Development Studies, Vol. 12. United Nations Center for Regional Development. Chakraborty, L. (2010a). Determining gender equity in fiscal federalism: Analytical issues and empirical evidence from India (Working Paper No. 590). Levy Economics Institute. Chakraborty, L. (2010b). Gender-sensitive fiscal policies: Experience of ex-post and ex-ante gender budgets in Asia-Pacific. UNDP. Chakraborty, L. (2016a). Asia: A survey of gender budgeting experiences (Working Paper 16/150). International Monetary Fund. Chakraborty, L. (2016b). Fiscal consolidation, budget deficits and macroeconomy: Monetary-fiscal linkages. Sage Publications. Chakraborty, L. (2020a). Macroeconomic policy coherence for SDG 2030: Evidence from Asia Pacific (Working Paper no. 292). National Institute of Public Finance and Policy. Chakraborty, L. (2020b). Fiscal prudence for what? Analysing the state finances of Karnataka (Working Paper no. 293). National Institute of Public Finance and Policy. Chakraborty, L. (2020c). Fiscal consolidation ex-post the escape clause: A call for excessive deficit procedure (Working Paper no. 299). National Institute of Public Finance and Policy. Chakraborty, L. (2021). Macroeconomic Framework of Union Budget 2021a–22: Reconsidering the fiscal rules (Working Paper No. 328). National Institute of Public Finance and Policy. Chakraborty, L., Ingrams, M., & Singh, Y. (2017). Effectiveness of gender budgeting on gender equality outcomes and fiscal space: Evidence from Asia Pacific (GRoW Research Paper WP 2017–09). McGill University. Chakraborty, L., Ingrams, M., & Singh, Y. (2018). Fiscal policy effectiveness and inequality: Efficacy of gender budgeting in Asia Pacific (Working Paper no. 224). National Institute of Public Finance and Policy. Chakraborty, P. (2021). COVID-19 context and the fifteenth finance commission: Balancing fiscal need and macroeconomic stability. Economic and Political Weekly, 33(14). Chakraborty, P. & Chakraborty, L. (2016). Beyond fiscal prudence and consolidation. Economic and Political Weekly, 51(16).
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Chattopadhyay, R. & Duflo, E. (2001) Women as policy makers: Evidence from a randomized policy experiment in India (Working Paper No. 01-35). MIT Department of Economics. De Mello, Jr., L. R. (2000). Fiscal decentralization and intergovernmental fiscal relations: A cross-country analysis. World Development, 28(2). Forster, C. (2018). Gender equality and federalism. 50 Shades of Federalism. Habibi, N., et al. (2003). Decentralization and human development in Argentina. Journal of Human Development, 4(1). Hinojosa, L., Bebbington, A., Barrientos, A., & Addison, T. (2010). Social policy and state revenues in mineral-rich contexts. Social Policy and Development Programme Paper 44. United Nations Research Institute for Social Development (UNRISD). Isaac, T. & Chakraborty, P. (2008). Intergovernmental transfers: Disquieting trends and the thirteenth finance commission. Economic and Political Weekly, 43(25). Kaur, A., Mohanty, R., Chakraborty, L., & Rangan, D. (2021), Ecological fiscal transfers: Any evidence for flypaper effects?. Paper presented at the International Institute of Public Finance Conference, University of Iceland, August 18, 2021. Klasen, S. (1994). Missing women reconsidered. World Development, 22, 1061– 1071. Klasen, S. (2008). Missing women: Some recent controversies on levels and trends in gender bias in mortality. Ibero America Institute Discussion Paper No. 168. Klasen, S., & Claudia, W. (2003). Missing women: Revisiting the debate. Feminist Economics, 9, 263–299. Kynch, J., & Sen, A. (1983). Women: Well being and survival. Cambridge Journal of Economics, 7 (3/4), 363–380. Litschig, S. & Morrison, K. M. (2013). The impact of intergovernmental transfers on education outcomes and poverty reduction. American Economic Journal: Applied Economics, 5(4). Lu, X. (2011). Do intergovernmental transfers enhance local education spending in China?. APSA 2011 Annual Meeting Paper. Musgrave, R. A. (1997). Devolution, grants and fiscal competition. Journal of Economic Perspectives, 11, 4. Rao, M. G. (2018). Public finance in India: Some reflections. Decision: Official Journal of the Indian Institute of Management Calcutta, Springer; Indian Institute of Management Calcutta, 45(2). Rao, M. G. & Singh, N. (2007). The political economy of India’s fiscal federal system and its reform. Publius: The Journal of Federalism, 37 (1). Oxford University Press. Winter.
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CHAPTER 6
Fiscal Decentralization and Ex Ante Gender Budgeting: Case Studies of Selected Countries Including India
Federations are seen as an “indestructible union of indestructible states”. A federal political order is here taken to be “the genus of political organization that is marked by the combination of shared rule and self-rule”. Fiscal federalism is the assignment of revenue and expenditure across various tiers of government and the design of intergovernmental fiscal transfers to correct the vertical and horizontal imbalances (Chakraborty, 2020a; Reddy & Reddy, 2019). In countries with very large heterogeneous populations, the central government cannot make efficient fiscal decisions for each and every local government (Bahl, 2008). There is greater potential for fiscal equalization under fiscal federalism (Bahl, 2008; Blöchliger, 2014). With greater fiscal decentralization, variations in fiscal capacities across local jurisdictions can be adjusted to provide an adequate level of public services provisioning without levying unduly high tax rates. This necessitates some form of fiscal equalization to ensure interjurisdictionally adequate finances to meet their public expenditure needs (Bahl, 2008). The principle of subsidiarity states that fiscal federalism is good for efficiency and equity in the economy based on the rationale that local governments, which are closer to citizens, are more efficient in the provisioning of public services than the higher levels of government (Oates, 2001). This rationale holds good in terms of gender development, as local governments have better information on gender differentials regarding © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 L. S. Chakraborty, Fiscal Policy for Sustainable Development in Asia-Pacific, https://doi.org/10.1007/978-981-19-3281-6_6
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needs and preferences. There can be hardly two opinions on the fact that the new-found policy space of feminization of local governance in India, coupled with fiscal devolution to the third tier, may provide an impetus to adopt the gender lens more effectively in formulating gender-sensitive fiscal policies. It could be based on dual conjectures. Firstly, greater fiscal autonomy at the local level, with effective feminization of governance, can make a transition in the budgetary decisions by incorporating gender concerns. Secondly, it helps to identify spatial gender needs, which is a step ahead from existing homogeneous one-size-fits-all gender budgeting policies. This chapter provides case studies of local level ex ante gender budgeting experiences. Gender budgeting, as mentioned earlier in the book, is an ex ante and ex post process. An ex-post gender budgeting is an application of gender lens to existing budgetary framework to understand the intensity of gender allocations in the budget and also to analyze the benefit incidence of public expenditure, with a thrust on care economy. At the decentralized levels of government, gender budgeting can be an ex-ante process through the identification of gender needs and incorporate them in budget. Bird and Vaillancourt (2006) explained the three different approaches within fiscal federalism: deconcentration, delegation, and devolution. Deconcentration occurs not through the transfer of any powers or authority to the local or regional offices, but when the central government delegates public service responsibilities to regional or local offices of the central government. In unitary countries, fiscal decentralization occurs in the form of deconcentration as there is no autonomous local governments to deliver services. Deconcentration also exists in fiscal federalism where the federal government is interested in making sure particular services are being delivered across the country (Escolano et al., 2012). Devolution involves the transfer of expenditure functions and finance to locally elected governments. This form of fiscal decentralization is concerned with “who has done at what level” in the sense who collects what taxes and who undertakes expenditure functions. It is also to deal with vertical and horizontal fiscal imbalance, which results from the devolution of expenditure functions and finance (Escolano et al., 2012).
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Fiscal Decentralization and Gender Frameworks The theoretical underpinnings of the rationale of incorporating gender into intergovernmental fiscal transfers are accountability (“voice” and “exit”), information symmetry, transparency, and appropriate size of government at the local level for effective service delivery. The degree of accountability (“voice”) in integrating gender in an intergovernmental fiscal setup is based on dual conjecture—first, the accountability of the subnational government to the higher tier of government and second, to the electorate. The former limits the latter, especially in cases where financial decisions are centralized, but the provision of public goods is decentralized. The separation of finance from the functional assignment can lead to inefficiencies, the most oft-cited problem being unfunded mandates. On the other hand, the real autonomy in the decision making of the Elected Women Representatives (EWR) plays a crucial role in integrating gender-specific needs in the fiscal policies and their accountability to the electorate gets constrained if the flow of funds is through deconcentrated intermediate levels with accountability to the central government. However, fiscal policy in a federal setting promotes government accountability, particularly in geographically or demographically large nations (Stern, 2002). Participatory local governments are generally better informed about the needs and preferences of the local population than the central government is and is the entry point of integrating gender concerns. It helps to improve efficiency in resource allocation, minimize transaction costs in designing and implementing the development policies, and ensure better incentive mechanisms and accountability. In fiscal federal setup, monitoring and control of governance by local communities is easier in principle. At the subnational level, elected governments can be expected to be generally more accountable and responsive to the gender concerns, and more effective in involving the women in the sociopolitical development processes. Decisions at the subnational level give more responsibility, ownership, and, thus, incentives to local agents and local information can often identify cheaper and more appropriate ways of providing public goods (Bardhan & Mookherjee, 1999; Stern, 2002). Another risk of incorporating gender in the intergovernmental fiscal transfer mechanism is the dominance of elite groups within the jurisdiction and their influence in control over financial resources and in the public expenditure decisions related to the provisioning of public goods and governance. There is growing evidence that power at the local level is
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more concentrated, more elitist, and applied more ruthlessly against the poor than at the centre (Griffith, 1981). This is referred to as elite capture in the theoretical literature. In such a setting, the voice of women elected as representatives may get neutralized by political pressure groups. In addition, if the women in governance are comparatively less empowered, with minimum/no education and basic capabilities, their ad hoc decisions on the systems of public goods and services will not have any major impact on poor and needy women. The benefits of decentralized socioeconomic programmes would be captured by the local elite and, in turn, result in underinvestment in public goods and services for poor women. This is particularly true in the context of heterogeneous communities and underdeveloped rural economies (Bardhan, 1999; Galasso & Ravallion, 2000). The aberrations in voice may induce the possibility of greater corruption at local levels of government than at the national levels; in turn, corruption deepens capability deprivation. There is empirical evidence indicating that decentralization increases corruption and reduces accountability (Rose-Ackerman, 1997; Tanzi & Davoodi, 2000), however, empirical evidence favours the hypothesis that the participation of women in governance structure lessens the possibilities of corruption (Swamy et al., 2001). The gender differences in the incidence of corruption may range from personality traits (honesty, law-abiding), to the degree of access to networks of corruption, or to lack of proper knowledge of how to engage in corrupt practices. It may also be the case that voice may be a “proxy voice” if the elected women are not empowered and their male relatives operate the local bodies. However, effective participation of female representatives at the local level can change the priorities in budgeting, bring accountability, and ensure quality and efficiency of public goods and services. The axiom of “exit”, which provides yet another mechanism for accountability, refers to the mobility of population. Theoretically, citizens who are dissatisfied with the public provisioning of services by one local government can “vote with their feet” by moving to another jurisdiction that better meets their preferences (Tiebout hypothesis). In practice, there are many constraints on interjurisditional mobility, especially in case of women. In spite of these constraints, there are evidences of interjurisditional labour mobility by women for wage employment. This reveals that factors beyond local service provision in physical and social infrastructure
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often influence citizen’s decision about where to locate. Interjurisditional labour mobility may be an instrument of local accountability when citizens reveal their preferences by strengthening exit. A centrally determined one-size-fits-all gender policy cannot be a solution to redress gender inequities in a country with a vast population and heterogeneity across jurisdictions. Given the heterogeneity in the efficiency of public service provisioning across jurisdictions, it may be timely to consider the scope of asymmetric federalism in the context of incorporating gender into fiscal policies. Asymmetric federalism refers to federalism based on unequal powers and relationships in political, administrative, and fiscal arrangement spheres between the units constituting a federation. Asymmetry in the arrangements in a federation can be viewed both vertically (between central and states) and horizontally (among the states). If federations are seen as an “indestructible union of indestructible states”, and the central government and states are seen to exist on the basis of equality, neither has the power to make inroads into the defined authority and functions of the other unilaterally (Rao & Singh, 2004). One way of looking at this is the process of accreditation where the subnational governments who pass minimum standards in service and product delivery, as well as specific attributes of governance, could be given greater autonomy in functions and finance. This requires benchmarking the governance of subnational governments, which may catalyze horizontal competition among the states. It can ensure gains in efficiency and increase productivity through the “Salmon mechanism”, in which intergovernmental competition is activated by benchmarking the performances of other governments in terms of levels and qualities of services, levels of taxes, or more general economic and social indicators (Salmon, 1987, as cited by Breton and Fraschini [2004] and Rao [2006]). The voters and opposition parties compare the supply performance of their governments with the benchmark performance and influence supply decisions (Breton, 1996; Salmon, 1987). This gender-sensitive benchmarking of local governance can empower women to compare the relative performance of their governments in terms of the tightness of “Wicksellian connections” and influence supply decisions of their jurisdictions to design and implement appropriate policies and programmes to ensure gender equity. A Wicksellian connection is a link between the quantity of a particular good or service supplied by centres of power and the tax price that citizens pay for that good or service. Knut Wicksell (1896)
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and Erik Lindahl (1919) showed that if decisions regarding public expenditures and their financing were taken simultaneously and under a rule of (quasi) unanimity, a perfectly tight nexus between the two variables would emerge. Breton (1996) argued that competition between centres of power, if it was perfect and not distorted by informational problems, would also generate completely tight Wicksellian connections. In the real world, competition is, of course, never perfect and informational problems abound; as a consequence, Wicksellian connections are less than perfectly tight. Still, as long as some competition exists, there will be Wicksellian connections (Breton & Fraschini, 2004). Intergovernmental competition and the mechanism of exercising choice by the citizen-voters, either through the exit or by voice, helps to reveal preferences of public services. The theoretical literature elaborated that competition results in innovations in the provision of public services and, in respect of public goods, it helps to identify the beneficiaries and impose user charges on them. However, the efficiency in the service delivery and welfare gains accrued and the enhancement of accountability depends on the nature of intergovernmental competition and political institutions (Breton, 1996). Information symmetry is one of the important factors in holding subnational governments accountable. When policymakers are in close proximity to the people they serve, the information they receive tends to be more accurate regarding the needs and demands of citizens across gender as they participate effectively and exercise their voice in terms of revealing preferences. The higher the information symmetry, the higher the accountability and transparency of the local government. Information symmetry can reduce the transaction costs on both the provider’s and the citizen’s side. The size of the lowest tier of the government varies significantly across countries. It is often argued that the smaller the size of the local government, the higher the inefficiency in public service delivery. It is often because of a lack of capacity to manage all the functions assigned to them. On the other hand, the smaller the size of local governments, the greater the participation and accountability become. The real challenge at this point is a judicious structure of local government that is not only politically acceptable, but also can provide efficient delivery of public services. The appropriate scale for key services should be an important element in the governance structure at the local level.
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There is no direct attempt so far to incorporate gender concerns in the intergovernmental fiscal relations in India. Given the asymmetries in the assignment of functions and finance, a significant prerequisite of integrating gender into intergovernmental transfers is to lessen the unfunded mandates. However, it is also important to gender sensitise the transfer system, as a major share of local government revenue is fiscal transfers. The point to be noted here is that it would be ideal to incorporate gender in specific-purpose transfers (conditional) rather than in generalpurpose transfers (unconditional). The objective of the general-purpose transfer system is to offset the fiscal disabilities and it is desirable to keep the transfer system formula-based, simple, equitable, and without perverse incentives. Any attempt to include a gender component in generalpurpose transfers may make it complex and create incentives against undertaking measures to improve gender equity. On the other hand, the objective of specific-purpose transfers is ensuring minimum standards in access to specified services, such as basic education, healthcare, water supply, sanitation, and anti-poverty interventions. Ideally the transfer system for gender equity should have a judicious mix of both general-purpose and specific-purpose transfers. The objective of the general-purpose transfers is to enable all subnational jurisdictions to provide normatively determined standards of public services. On the other hand, it is important to design specific transfers to implement direct programmes that would enhance the capabilities and entitlements of women, which, in turn, would help them to release the time locked up in the unpaid activities of the care economy and enable them to participate in paid work in the market economy. Despite the enormous literature on federalism in constitutional design, and the growing attention to gender equality in constitutional design, there has been remarkably little attention paid to the interaction between the two. Ryan (2017) argues that political participation by women is central to the development and argues for the recognition of opportunities for women in leadership, political participation, and the strengthening of democracy at the level of subnational governments. Ryan (2017) presents a cross-country analysis of increasing political participation by women in formal political structures and processes in the subnational governance. The rationale of fiscal federalism is based on the following conjectures: (Chakraborty, 2010)
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● Provide greater fiscal autonomy at the local level, with transition in the budgetary decisions and intergovernmental fiscal transfers by incorporating gender concerns. ● Helps to identify special gender needs, unlike one-size-fits-all gender budgeting policies. ● It is also significant for the redistribution objectives between regions, which helps cement a diverse nation. The fiscal decentralization of gender policies holds good, as local governments have better information on gender differentials regarding needs and preferences. Decisions at the subnational level give more responsibility, ownership, and, thus, incentives to local agents and local information can often identify cheaper and more appropriate ways of providing public goods (Bardhan & Mookherjee, 1999; Stern, 2002). The genesis of these debates on how to translate gender commitments into fiscal commitments can be traced to “gender budgeting” experiments—the analysis of the budgets through a “gender lens”—as a tool of accountability ( Chakraborty, 2020b, 2020c, 2020d; Kolovich, 2018). Gender perspectives engage many types of issues: political reforms to increase women’s representation, extending universal rights and social citizenship benefits to women, and establishing gender rights (Vickers, 2013). In the multi-level fiscal federalism in India, the political economy process of gender in fiscal mechanisms may pass through four distinct phases—innovative knowledge networking, building institutional structures, reinforcing state capacity, and strengthening the accountability mechanisms, at national and subnational levels (Chakraborty et al., 2020; Vickers, 2013). The analytical matrices for categorizing public expenditure through a gender lens were identified as follows: (Chakraborty, 2014) 1. Specifically, targeted expenditure to women and girls; 2. Pro-women allocations, which are the composite expenditure schemes with a significant women’s component; and 3. Residual public expenditures that have gender–differential impacts.
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However, these analyses more often get confined to the top level of the government. Identifying the gender issues in fiscal federalism requires acknowledgement of intergovernmental fiscal transfer mechanism. Intergovernmental fiscal transfers are used as a tool for addressing the horizontal and vertical imbalances in fiscal federalism, and incorporating gender as criteria of these transfers can increase the progressivity of the transfers (Anand & Chakraborty, 2016). The revenues of subnational government are twofold. One is intergovernmental fiscal transfers. Two, the own revenue handles of the subnational governments. These own revenue policies and intergovernmental transfers are not gender-neutral.
Third Tier Institutional Details: Fiscal Devolution Through a Gender Lens India is the largest democratic federal polity in the world. Out of over a quarter-million local governments, only around 3000 are in the urban areas. Structurally, decentralization in India would seem to have been carried to the smallest unit of habitation viz., villages, but their resources and functions are limited. While substantial resources are raised or are devolved further to the second level viz., the states, the third tier suffer acutely from inadequacy of resources. Although constitutional amendments provide an illustrative list of functions that are considered appropriate for local governments, they remain largely unfunded mandates (Box 6.1). The amendments also made it mandatory to appoint a state finance commission once in every five years to make recommendations regarding the fiscal transfers from the state to the local bodies; progress in terms of functions and finance to local bodies has been tardy. The degree of decentralization in any country is difficult to quantify. Fiscal decentralization can broadly be captured by the share of subnational expenditure in total expenditure and/or local government expenditure as a percentage of the GDP of the country. However, these indices do not capture enough of the governance structure to understand the degree of power in terms of decision-making vested with the local government over expenditure functions. Lack of data on these components of governance structure limits the empirical analysis to a great extent.
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Box 6.1: 73rd and 74th Constitutional Amendments
The 73rd and 74th Constitutional Amendments, regarding the local self-governments in India were passed by Parliament in December, 1992. The 73rd Constitutional Amendment Act, 1992 came into force on April 24, 1993 and 74th Amendment Act, 1992 on June 1, 1993, thereby the Local bodies—“Panchayats” and “Municipalities” came under Part IX and IXA of the Constitution of India. The Salient Features of the 73rd and 74th Constitution Amendment Acts. The Panchayats and Municipalities will be local self-governments, with Grama Sabha (villages) and Ward Committees (Municipalities) as the basic units of democracy. All adult members are registered as voters. Except in the States where population is below 20 lakhs, there will be three-tier system of panchayats at village, intermediate block/taluk/mandal, and district levels (Article 243B). The seats at all levels to be filled by direct elections [Article 243C (2)]. The seats reserved for Scheduled Castes (SCs) and Scheduled Tribes (STs) and chairpersons of the Panchayats at all levels also shall be reserved for SCs and STs in proportion to their population. One-third of the total number of seats to be reserved for women. One-third of the seats reserved for SCs and STs also reserved for women. One-third offices of chairpersons at all levels reserved for women (Article 243D). Uniform five year term and elections to constitute new bodies to be completed before the expiry of the term. In the event of dissolution, elections compulsorily within six months (Article 243E). Independent Election Commission is constituted in each State for superintendence, direction, and control of the electoral rolls (Article 243K). Panchayats have to prepare plans for economic development and social justice in respect of subjects as devolved by law to the various levels of Panchayats including the subjects as illustrated in Eleventh Schedule (Article 243G). The 74th Amendment provides for a District Planning Committee to consolidate the plans prepared by Panchayats and Municipalities (Article 243ZD). The funds constitute the budgetary allocation from State Governments, share of revenue of certain taxes, collection and retention of the revenue it raises, Central
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Government programmes and grants, Union Finance Commission grants (Article 243H). State Finance Commissions determine the financial devolution principles for panchayats and municipalities (Article 243I). Source www.india.gov.in.
The available estimates showed that the local government expenditure as a percentage of GDP constituted 2.20 percent, while in terms of revenue mobilization, local government revenue constituted 0.54 percent of GDP. Specifically, over a quarter-million rural local bodies in India mobilize only 0.04 percent of GDP. The expenditure of local government constituted 7.90 percent of the total, but their revenues accounted for only 2.73 percent of the total. The available estimates on the fiscal autonomy ratio of local governments (the ratio of own revenue to total expenditure) was as low as 27 percent in India. In the case of low-income states, it was even lower at 13.03 percent (Rao et al., 2004). Given that a major part of the subnational government revenue accrues from fiscal transfers, the attempt of gender budgeting at the local level in India does not go far enough unless the institutional mechanisms of fiscal decentralization and degree of fiscal autonomy are varied. There is a lack of transparency and accountability in the system because of the extensive use of inadequate revenue assignments, lack of sufficient decentralization to local bodies, and a poorly designed intergovernmental transfer system. However, as local governments depend heavily on transfers from the higher level of government, could engendering the criteria of fiscal devolution be a plausible policy step? Chakraborty et al. (2018) analyze the fiscal transfer architecture in India, incorporating the various components and channels of transfers. In India, IGFT can be broadly categorized into conditional and unconditional transfers. The first channel of unconditional transfers consists mainly of the Finance Commission formula-linked tax transfers from the Union’s pool of revenues. The second channel of conditional transfers consists mainly of grants from the Finance Commission and from line ministries of the Union government (or centrally sponsored schemes). India has a three-tiered federal structure, with 29 state governments and 7 centrally administered Union Territories and more than a quarter million local self-governments in states, in both rural and urban areas. The richest
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province is Goa, with a per-capita income of INR 270,150 and poorest province is Bihar, with a per-capita income of INR 34,168, as per the Central Statistical Office data for the year 2015–2016 (Chakraborty et al., 2018). Among the criteria of fiscal devolution to the third tier, population turns out to be the predominant one. It is true that population criterion has an advantage of providing a summary measure of the basic needs that is free from value judgement and arbitrariness, unlike other indicators. However, heavy reliance on too broad a measure of need (like population) could be inconsistent with promoting fiscal equalization or balanced development of regions within a state. Gulati (1987) pointed out that population as a basis of distribution altogether ignores the existence of income disparities among the states. As an alternative to that, he argued, would be the distribution of resources on the basis of per capita income; this would be much more even and fiscally equalizing. Population criteria apart, all three SFCs have considered applying other indices of socioeconomic backwardness for the horizontal distribution of resources. While selecting the criterion of backwardness, one has to be very careful so that it does not suffer from arbitrariness and excessive value judgment. The question arises at this juncture whether objective indicators of economic and social infrastructure could also be used for assessing the backwardness of a local body. The Twelfth Finance Commission (TFC) has incorporated indices of deprivation including the percentage of households fetching water from a distance and percentage of households without sanitation. Public investment in infrastructure like water supply and sanitation can have positive social externalities in terms of educating the girl child and improving the health and nutritional aspects of the household. A World Bank study (Bredie & Beehary, 1998) noted that easy accessibility to drinking water facilities might lead to an increase in school enrolment, particularly for girls; in Madagascar, 83 percent of the girls who did not go to school spent their time collecting water, while only 58 percent of the girls who attended school spent time collecting water. However, the major criticism against the use of social indicators as an index of backwardness is that it will be biassed against the regions that, despite poor resource base, have achieved relatively high levels of attainment in these sectors. Do fiscal equalization transfers enhance gender equity? Though these transfers are not specifically targeted to the poor, the poor will benefit from the general capacity increase in the region, especially women. When
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unconditional transfers are made, equalization transfers aim to neutralize deficiency in fiscal capacity, but not in revenue effort. Sometimes adjustments affecting cost and need factors may also be accommodated. In many ways, the finance commission’s formula-based fiscal transfers are not part of an equalization grant system, but rather part of general or unconditional funding, which might have equalization grant features. Chakraborty (2003) seeks to empirically investigate if the fiscal transfers in India follow the principles of fiscal equalization. Econometric investigation using panel data for 15 major states for the years 1990–1991 to 1999–2000 in a fixed effects model revealed a strikingly regressive element of transfers, with aggregate tax transfers per capita positively related to state per capita income. However, grant transfers showed clear progressivity, though the grant transfers are not sufficient to eliminate horizontal inequalities owing to a smaller proportion of grants in the overall transfer in comparison to tax transfers. His results echo those of previous studies, reinforcing the oft-made observation that richer states are receiving more per capita fiscal transfers than poorer states. Fiscal equalization grants can correct for spatial inequalities in the provisioning of merit goods or quasi-public goods, which have evident gender differential impacts. Considering the acute spatial disparities in service standards in the provision of health and education, the TFC has tried to bring in the equalization principle for certain specific grants for education and health on the expenditure side. Although equalization should be pursued mostly, if not exclusively, by the equalization grant system in order to free up other grant instruments to pursue other objectives, this is a temporary positive move given the present need for more equalization in the system (Bahl et al., 2005). Fiscal equalization grants for health and education can redress the capability deprivation across gender. The moot question at this juncture is whether gender criteria needs to be incorporated in the unconditional fiscal transfers. One of the arguments against incorporating gender concerns in unconditional fiscal transfers is that these transfers are meant for offsetting the fiscal disabilities and it is desirable to keep the transfer system formula simple and without perverse incentives (Rao, 2006). However, in India, given the disturbing demographic facts of the precipitous decline in the sex ratio for children in the 0–6 age group, especially in some of the prosperous states of India, there can be no valid objection to using central transfers for this purpose. A simple method for this could be to introduce
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some weight for the female population of the states in the tax devolution formula of the finance commission (Anand & Chakraborty, 2016; Bagchi & Chakraborty, 2004; Chakraborty, 2010, 2020a). The message would be even stronger and more appropriate if the population of girl children only, that is the number of females in the 0–6 age group, is adopted as the basis for determining the relative shares of the states in the amount carved out of the divisible pool by applying the allotted weight. A special dispensation for girls would also be justifiable in a scheme of needbased equalization transfers. The Fifteenth Finance Commission has used Total Fertility Rate as a criterion to correct for the demographic transition effects, which is indirectly a gender-related criterion (Chakraborty, 2020a). While social mores cannot be changed by fiscal fiats, especially when prejudices run deep, state action is called for when they are blatantly oppressive to any section of the community. Indeed such action is an imperative. The transfer system can and should play a role in upholding the right to life for the females of the country (Bagchi & Chakraborty, 2004; Chakraborty, 2010, 2020c). Having said that, it needs to be mentioned that it is not plausible to incorporate more gender variables in the formula and complicate the transfer formula of the Finance Commission. In other words, inclusion of a gender inequality index in the transfer formula may not result in the intended results, as the variables included in the index may neutralize each other. Specifically, the empirical evidence on fiscal decentralization and gender arrives at the following four inferences. One, fiscal federalism prima facie does not ensure gender equality. Two, with the advent of federal governance and fiscal decentralization, significant expenditure functions that are important for gender equality such as health care, education, and income-support programmes are given importance in fiscal federal design. The infrastructure investment, though rich in potential, has not effectively been analyzed through a gender lens. Three, the fiscal allocations relate to the labour market that may promote women’s economic empowerment need an emphasis. Four, the design of the tax system and tax policy are relevant to gender equality, however, evidence suggests that differential tax system cannot correct gender inequalities. Five, fiscal federalism arrangements such as specific-purpose grants to subnational governments can promote gender equality.
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Fiscal Decentralization and Local Level Gender Budgeting: Case Studies Despite the initiatives to integrate gender at various tiers of government within the federal structure, a major lacuna of such policy initiatives have been to integrate gender in intergovernmental fiscal transfers to the local level government. How gender budgeting can serve as a potential instrument to pursue gender equality objectives in a federal fiscal system can be twofold. One, adopting gender budgeting is usually a central component of gender equality agendas across federations. Two, in a federal context, gender budgeting needs to be adopted at all levels of government and must ideally be implemented using a common framework across subnational units to facilitate the assessment of relative performances and possibly strengthen subnational governments’ incentives. A detailed comparative perspective is given by providing a few examples on gender budgeting at various tiers of government from the experiences of selected federal countries. Downes et al. (2017) provides gender budgeting initiatives in a few federal countries in OECD such as Australia, Canada, Austria, Spain, India, and South Africa. A further investigation of how selected countries have implemented gender budgeting as part of their local level budgetary framework is briefly attempted in this section for selected countries like The Philippines, Morocco, India, South Africa, Ethiopia, and Nepal. The Philippines The Nation-State of the Philippines is an archipelago of 7100 islands and home to people speaking as many as 87 dialects. This probably explains why historically, the political structure of the Philippines had been of a much decentralized nature—each barangay or village was ruled by its own chieftain, spoke its own dialect, and formulated its own laws based on tradition and needs. These rudiments of the decentralized system in the Philippines were strongly affected by the period of colonial domination. Centralized ruling structure has been the prominent characteristic legacy of Spaniards, the Americans, and the Japanese conquest of this country. However, since independence in 1946, the Philippines has been gravitating more towards decentralization. In the period of Third Republic (1946–1972), many laws related to the local autonomy were enacted, viz., Local Autonomy Act of 1959 and the Decentralization Act of 1967,
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to grant fiscal and regulatory powers to the local governments. The 1973 Constitution also made it mandatory for the state to “guarantee and promote the autonomy of the local governments to ensure their fullest development as self-reliant communities”. However, twenty years of authoritarianism in the form of martial rule acted as a barrier to the attempts towards decentralization. Termination of this era saw the re-emergence of democracy through people’s empowerment. Substantive process of fiscal decentralization started in the Philippines with the enactment of Local Government Code (LGC) in 1991. The LGC institutionalized systematic allocation of powers and responsibilities between the national and local governments. Though fifteen years into the implementation of the Code, integrating gender in the planning and budgetary policies at the local government is however relatively a new approach in the Philippines. At the national level, gender budgeting policy initiatives started in the Philippines with the Gender and Development (GAD) budget in 1995. The GAD budget made a provision for earmarking at least 5 percent of all departmental expenditure on programmes for women in national and subnational budgets. However, fixing the floor limits for spending on gender resulted in the misallocation of resources in various departments. It also resulted in the marginalization of gender issues in the mainstream budgeting, as floor limits have been taken as ceiling in various departments. In this context, it needs to be highlighted that earmarking a specific proportion of budgetary allocation for women is only a second best principle of gender budgeting and may not be the most appropriate tool to sensitize budget through gender lens. There was no penalty for not utilizing the GAD budget fully and efficiently, many of the departments ended up with unspent surplus in the GAD budget. Ideally, differential targeting of expenditure emanating from the identification of appropriate programmes for women in various sectors or reprioritising the expenditure based on a generic list of appropriate programmes and policies for women might be more effective than uniform targeting at 5 percent across sectors. However, with the strengthening of the fiscal decentralization process in the Philippines, local government units (LGUs) were provided with more opportunities in terms of local level gender budgeting and challenges as well. The devolution of basic functions like health, social welfare, and agricultural extension to the LGUs, created more space for the local government units (LGUs) to incorporate the gender needs at the local level. Some of the LGUs have indeed used this opportunity to initiate gender-responsive policies at local
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level. However, as devolved functions were largely unfunded mandates and the intergovernmental transfers and budgetary process at the local level were largely politically determined, they posed serious challenges for effective decentralization and in turn local level gender budgeting initiatives. Local level gender budgeting initiatives in the Philippines can be found in a few barangays, particularly in Sorsogon and Hilongos, where selective attempts were made to identify specific gender needs before budgeting. These initiatives, which came from the Department of Interior and Local Government (DILG) and National Commission on the Role of Filipino Women (NCRFW) along with the UNIFEM in the year 2004, moved ahead from quota-based gender budgeting to the identification of entry points for results-oriented gender-responsive budgeting. However, local level gender budgeting has been highly a sectoral process in the Philippines. In Sorsogon, the initiative is in the health sector; where gender-related MDG health goals have been identified and budgeted. In Hilongos, the initiative has been in the agriculture sector. Prima facie, agriculture sector appears to be a gender-neutral sector. But it was identified that strengthening the agricultural sector has clear gender differential impacts in terms of reducing the forced migration of women and also in enhancing their income-earning opportunities. India India has made history as the first country ever to integrate gender in the intergovernmental fiscal transfers (IGFT) formula. The 15th Finance Commission has taken this bold decision—during its transition to use the population data 2011 instead of 1971—not to penalize the states with better demographic performance. The 15th Finance Commission’s decision to give 12.5 percent weightage to “demographic performance” is laudable. The Commission has decided to use total fertility rate (TFR)— instead of other plausible indicators like female population of the states or the sex ratio of 0–6 age group—as an indicator of “demographic performance”. The 15th Finance Commission report tabled in Parliament on February 1, 2021 noted that the reduction of TFR—the average number of children that would be born to a woman over her lifetime— also reflects better performance in maternal and child health as well as education, and it reflects quality of human capital. It remains an empirical question whether incorporating TFR or a sex ratio (0–6) makes Finance
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Commission transfers more progressive/equitable. Conducting a progressivity analysis is significant to know whether TFR is a better criterion than the other in capturing the “demographic performance”. It is interesting to recall here that in United Nations Gender Inequality Index (GII) which has been published every year since 2010, adolescent fertility rate is incorporated as one of the parameters to reflect the “reproductive health” gender dimension. That being said, it needs to be mentioned that it is not plausible to incorporate more demographic variables in the Commission’s already complex tax transfer formula. The inclusion of UN’s “gender inequality index” in the tax transfer formula—instead of one single indicator—may not result in the intended results, if the variables included in the index may “neutralise” each other. The genesis of these debates on how to translate the gender commitments into fiscal commitments can be traced to gender budgeting experiments as a tool of accountability. The pioneering study by the National Institute of Public Finance and Policy led to developing analytical matrices to “engender” the budgets. In 2004–2005, through accepting the recommendations of “Classification of Budgetary Transactions” Committee institutionalizing gender budgeting became a reality in India. As a prelude to this, the Economic Survey in 2000–2001 also, for the first time ever, carried a chapter on “gender”, drawing the gender diagnosis from NIPFP study. However, integrating gender in macroeconomic policies has largely confined to the domain of public expenditure at the Centre and state levels. In a fiscal federalism like India, unless we “engender” the IGFT mechanisms, the picture remains partial. With the bold decision by the 15th Finance Commission to integrate gender criterion in general purpose transfers, a great leap forward is thus made. In addition to incorporating gender criteria in tax transfer formula, it is argued that finance commissions should design specific purpose transfers to strengthen the gender budgeting initiatives at the subnational levels, including the third tier. With the advent of fiscal decentralization aftermath 73rd and 74th Constitutional Amendments and the feminisation of local governance in India (33 percent reservation for women), the imperative for gender equity will be even stronger if the specific purpose transfers can facilitate integrating the revealed preferences (“voice”) of women in local level public expenditure decisions. Identifying transformative financing for gender equity is the clause 5c of Sustainable Development Goals (SDGs). Kerala has a rich experience on the local level gender budgeting.
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State level gender budgeting in India has also used the national level analytical matrices and templates. For instance, a successful example of subnational level gender budgeting was adopted by the State of Karnataka in 2006–2007. In line with the NIPFP methodology, Karnataka has successfully institutionalized gender budgeting within its Ministry of Finance. The Comptroller and Auditor General report mentioned that the Finance Department of Karnataka has followed the Lahiri committee recommendations on fiscal matrices and classification of budgetary framework in categorizing the allocations (Government of India, CAG report [Report 1] on State Finance, Karnataka, 2013). Intense consultations with field officers of 21 Secretariat Departments and 34 Administrative departments led to the first gender budget statement in Karnataka. Data paucity was a major constraint in validating the classifications of spending. The challenge was to obtain disaggregated data and identify the flow of funds for monitoring and evaluation. At the state level, Kerala was also a leader in institutionalizing gender budgeting in 2008. The “Kerala Model” of development which is widely referred to in the development economics literature refers to a peculiar situation where human development indicators are good compared to a low level of per capita income. Against the backdrop of the budget announcement in 2006, the state government entrusted the Centre for Development Studies Unit on Local Self Government to undertake a study of state-level gender budgeting. A report entitled “Analysis of Kerala State Budget 2007–2008 Through a Gender Lens” was prepared and submitted to the Finance Minister in February 2008. This Centre for Development Studies Report not only attempted an ex-post gender analysis of the Kerala State Budget 2007–2008, but also provided a roadmap for institutionalizing gender budgeting within the Kerala Department of Finance, thereby introducing a Statement on Gender Budgeting in the budget documents. Subsequently, a significant move in this direction began in Kerala with the announcement by the Finance Minister in his Budget Speech 2008 that from next year onwards a special Statement on Gender would be submitted to the legislature along with the Budget, as is done at the central government, along with other policy announcements for institutional mechanisms. The Centre for Development Studies analysis also highlighted that there is no separate Ministry/Department for Women Affairs in Kerala. A new institutional structure named the “Gender Board” was announced in the 2008 Budget speech.
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A Gender Budget Statement of Kerala was extended by introducing allocations separately for infrastructure programmes (Government of India, 2015). It is also noted that 15–20 percent of local governments have undertaken studies on the Status of Women, as a prelude to gender planning at the local level (Government of India, 2015). In Kerala, democratic decentralization occurred in the mid-nineties, and a Women Component Plan (10 percent of State Plan Outlay) was earmarked to conduct gender budgeting at the third tier. The details of this process are provided in Isaac and Franke (2000), Isaac (2004), and Chakraborty (2004). In subsequent years, innovative projects related to gender in infrastructure projects have been consistently undertaken by the state government. For instance, in 2013, Kerala introduced She-Taxi to ensure safe mobility of women, driven by women, which has a database of all Emergency Response Systems in the city. Safe night shelters and hospitals are available for women, and vehicles are proactively monitored from a 24×7 Security Control Room. This is one of the flagship programmes of “Gender Park”, introduced by the Department of Social Justice, Government of Kerala, to engage in innovative research and development, capacity building, and innovative infrastructure projects for women’s security and empowerment. Gender Park was conceptualized by the former Finance Minister of Kerala, T. M. Thomas Isaac, and announced in his Budget Speech 2011–2012. Gender Park is the first such large scale initiative in India to reduce gender inequalities through innovative projects, though delayed in its full execution, it was officially inaugurated recently by the President of India in February, 2016. In 2019, Kerala has become the first state in India to implement the “She Pad” scheme aimed to distribute clean sanitary pads to all school students across the state with the support of local self-government institutions. Kerala In the backdrop of democratic decentralization, Kerala has been a pioneer state in India in moving towards gender-responsive planning and budgeting at local level. The simultaneous occurrence of feminization of political governance at the third tier with 33 percent representation of women created new democratic space for local level interventions by an agency of Women Elected Representatives (Isaac, 2004). Despite the remarkable achievements in terms of gender indicators in health and
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education, Kerala however has been experiencing extreme marginalization of women especially in the spheres of governance and work force participation. In other words, superior conditions of women in Kerala in terms of social indicators has had no impact on gender status. It was in this context that a deliberate attempt was made to incorporate the gender perspective into the process of democratic decentralization. Though it was only in 1991 that Kerala (like the rest of India) came to have elected bodies at the district level, the civil conditions of the state have been ideal for democratic decentralization reforms, since long. Widespread literacy, sharply reduced deprivation and absolute poverty, good health performance, successfully carried out land reforms, powerful class and mass organizations etc. have acted in synergy for Kerala as an ideal state for the introduction of participatory local democracy. Popularly known as the “Kerala Model”, the state has demonstrated how appropriate redistribution strategies can meet the basic needs for citizens despite low levels of economic development. However, Kerala has failed to translate high social sector achievements into comparable achievements in the material production sectors. This has resulted in economic stagnation of the state, growing unemployment, and an acute fiscal crisis thereby raising questions about the sustainability of the “Kerala Model”. Democratic decentralization, intended to accelerate economic growth and create a new model of growth with equity, has been the political response to the stagnating economy of the state. All 1214 local governments in Kerala—municipalities and the three tiers of rural local government—district, block, and gram panchayats were given new functions and powers of decision-making, and were granted discretionary budgeting authority over 35–40 percent of the state’s developmental expenditures. The democratic decentralization, however, attempted more than just devolution of resources and functions. Local governments were not only charged with designing and implementing their own development plans, they were mandated to do so through an elaborate series of participatory exercises in which citizens were given a direct role in shaping policies and projects (Isaac & Franke, 2000). Reversed Sequence of Decentralization In Kerala, the usual sequence of decentralization has been reversed; financial devolution preceded functional devolution. In 1996, 35–40 percent of the outlay of Ninth Five Year Plan was devolved to local self-government institutions. This financial devolution took place outside
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the purview of the State Finance Commission of Kerala. Given the low level of administrative capacity at the newly created third tier and the lack of experience of newly elected members of local bodies, the reversal of sequence of decentralization tended to create disequilibrium during plan implementation. However complementary reforms undertaken by the state government have created conditions for successful devolution. For instance, quite contrary to the rest of India where financial devolution took the form of schemes (tied in nature), in Kerala 75–80 percent of devolution has been in the form of untied grants-in-aid. Thus the nature of financial devolution in Kerala encourages maximum fiscal autonomy to the local governments. New Democratic Space for Gender Kerala reveals a paradox in terms of gender development. A much lower gender gap in social indicators and high female empowerment have accompanied Kerala’s remarkable performance in human development as demonstrated by several attempts to constructing the GDI and the GEM at the regional level for India. However, high rates of literacy and the dramatic decline in fertility did not translate into rapid growth of paid employment for women nor into upward occupational mobility. One of the reasons for this phenomenon is the sex-differentiated pattern of education. The electoral arena of Kerala has also been short of women’s representation. While in the state assembly the numbers elected have varied between 5 and 8 members in a house of 140 legislators since the early nineties, the proportion of women candidates hovered around 5 percent for the last two and a half decades. The process of democratic decentralization is expected to enhance the visibility of educated women in the public sphere with 33 percent representation for women at the local level. The total number of elected representatives was 14,173 of whom 75 percent belonged to the gram panchayats, that is, around 10.8 per gram panchayats. The analysis of characteristics of the women elected representatives revealed that only 10 percent of them had prior experience as elected representatives and only 18 percent had education above matriculation (Isaac, 2004). It is also revealed that while elected women representatives are better educated than their male counterparts (a social fact that is unique to Kerala in the Indian context), the women were on average younger, much less politically experienced, and inadequately equipped with basic knowledge of rules, regulations, and administrative issues.
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Moreover, women representatives have had to bear a triple burden of public office, income-earning activities, and domestic duties (Isaac & Heller, 2002). As part of the democratic decentralization, women elected representatives were given continuous capacity-building training programmes, which have helped them significantly to adapt to new challenges. A self-assessment survey of women elected representatives shows that their administrative knowledge and management skills, as well as their ability to officiate at public functions and interact effectively with their constituencies, have improved very significantly over the years (Isaac et al., 1999). There were two avenues through which democratic decentralization thus contributed to empowerment of women; (i) agency of women elected representatives (WER); and (ii) new democratic space for local level intervention by women. On the one- hand Kerala features extreme cases of marginalization of women despite remarkable development achievements, and on the other the state has introduced one of the most radical programmes on democratic decentralization, which makes Kerala an ideal case for studying the impact of fiscal decentralization on gender (Isaac, 2004). Identifying Spatial Gender Needs for Budgeting Yet another remarkable feature of democratic decentralization in Kerala was the noble attempt to incorporate the gender budgeting in the process through providing a Women’s Component Plan (WCP) by earmarking 10 percent of State’s Plan Outlay towards specifically targeted programmes for women. These programmes are determined by women at the local level through participatory process at gram sabhas (ward-level assemblies). The networks of neighbourhood groups and self-help groups were linked to gram sabhas to increase participation of women. With the constitutional provision for one-third reserved representation of women in Local Self Governments and the introduction of a special WCP amounting to 10 percent of the plan outlay, what has been the experience so far? The distinctive feature of the democratic decentralization in Kerala is the planning function of the local self-governments to identify the spatial gender needs, prelude to budgeting. In other words, as a statutory precondition for receiving the WCP from the state government, local governments must prepare a comprehensive area plan. This planning process includes holding gram sabhas, and convening sectoral task forces
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in which non-official experts and volunteers directly prepare reports, formulate projects, and draft sectoral plans. The various stages of plan preparation in effect represent new participatory spaces in which women, elected women representatives, and officials deliberate and prioritize developmental goals and projects. In order to ensure transparency and participation without compromising the technical requirements of planning, the planning process is divided into discrete phases with distinct objectives, key activities, and associated training programmes (Isaac & Heller, 2002). Though modifications to the sequence have been made every year, the basic model for incorporating the gender component in various stages of democratic decentralization in Kerala remains the same to design the WCP. Appraisal and Approval of Plans The major failure with regard to this experiment of incorporating gender budgeting in the democratic decentralization process was that the WCP for the first year did not meet targets, both in terms of overall allocation and the relevance of projects. The allocation for the WCP fell far short (4.26%) of the suggested minimum of 10 percent in the annual plans for 1997–1998. The share steadily declined as one moved up the tier (i.e. from GP to block panchayat and then to district panchayat). The proportion of Plan grant-in-aid was also low in WCP projects. Besides, there was not much difference in overall projects and WCP projects. The proportion of WCP that could be genuinely described as women development projects was also debatable. A few of these shortcomings were dealt with in the second annual year plan through a series of policy initiatives. First, more than the statutory minimum requirement of 10 percent of the plan grant-in-aid was earmarked for WCP in all districts. Second, an undue emphasis on credit and beneficiary contribution in women development projects was reduced and more realistic patterns of project financing were adopted during the second year. Third, the quality of projects improved. The tendency to include the general sector projects in WCP on the basis of notional (indirect) benefits to women has declined and the number of projects that specifically address the gender status of women has significantly increased (Isaac & Heller, 2002). It is also to be noted that changes were made in the role and functions of the WCP task forces. Clear guidelines were established to design
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WCP projects, moving away from WCP investing in economic infrastructure including roads, water, and sanitation to more microfinance programmes and small-scale industries. As a result of these measures, many weaknesses were rectified. Despite the initial disequilibrium with regard to gender budgeting at local level in the year of commencement, the spurious projects on gender disappeared in due course and “practical gender needs” projects became the building block for institutionalizing “strategic gender needs”. The experience of WCP projects in Kerala of moving away from economic infrastructure to microfinance programmes generates a debate on “specifically targeted programmes for poor” versus “infrastructure programmes”; particularly in terms of gender budgeting. An IFPRI study showed that public expenditure on road infrastructure has the largest impact on poverty reduction. In this context, it is to be noted that investment in infrastructure can catalyze the fulfilment of practical needs of women; however gender budgeting is required more for addressing the financial allocation and implementation issues related to the strategic needs of women. Microfinance sector, one of the areas which was given emphasis in WCP projects in Kerala through credit-linked self help groups (SHGs) in the later years, can ensure the strategic needs of women. Unlike in the Philippines, earmarking a definite proportion of budget for women has not led to marginalization of gender issues in the mainstream budgeting, as floor limits have not been taken as ceiling in case of Kerala. Rather, identifying the spatial gender needs ex-ante to budgeting led to allocation of more than the statutory minimum requirement of 10 percent of the plan grant-in-aid earmarked for WCP in all districts. Though WCP is considered as second best principle of gender budgeting, Kerala’s experience of linking WCP ex-ante to identifying local needs through the appropriate institutional mechanisms proves that it is tantamount to designing the gender budgeting based on differential targeting of expenditure emanating from the identification of appropriate programmes for women in various sectors or reprioritizing the expenditure based on a generic list of appropriate programmes and policies for women. Therefore Kerala experience of WCP is more effective than ad hoc uniform targeting as in case of the Philippines GAD budget as well as the national level WCP designed as part of the Ninth-Five-Year-Plan in India.
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Karnataka The standardized system of fiscal decentralization came to existence in Karnataka only after the 73rd Constitutional Amendment (1992) through the Karnataka Panchayati Raj Act (1993). It provided for a three-tier structure of rural local government with 27 zilla parishads, 175 block panchayats and 5659 gram panchayats. Although the process of decentralization has been effective and created wide possibilities for integrating gender needs at local level in Karnataka, the scope has remained largely unexplored. Unlike Kerala, there has been no within government initiative to conduct gender budgeting at the third tier in Karnataka. However, there has been a civil society initiative on “Building Budgets from Below” to examine whether the increased feminization of governance [in Karnataka, 44 percent of those elected to village panchayats are women, though the constitution provides for 33 percent] could alter the public expenditure decisions at the third tier in Karnataka. The first phase of the study revealed that devolved functions have remained largely as unfunded mandates and the elected women representatives (EWR) were not capable to explore their newfound powers in altering the budgetary priorities towards their needs. An attempt to rectify this lacuna was taken up in the second phase of the study through a technique of Janaagraha (community participation). An exclusive training was given to the EWRs as part of Janaagraha with regard to budgeting. It was revealed in the third phase of the study that EWRs were empowered to identify the spatial gender needs and arrive at the financial requirements, but their bargaining power in terms of altering the budgetary priorities remain dismal. The study found that EWR are frequently excluded from budget discussions, and the requests they made for funding of projects in their constituencies were given less priority than those made by men elected representatives. The study concluded that this happen because of gender discrimination and gender bias shown by the authorities while allocating works and distributing benefits. As a result, most women members could not undertake development works in their respective constituencies. The methodology adopted for this study, however, has certain limitations, due to non-inclusion of a simultaneous study of control groups to analyze the impact of Janaagraha and other training modules adopted in the second phase of the project. Also a longitudinal survey (at least two,
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a benchmark survey and an impact survey) would have been more beneficial to analyze the intertemporal effects of feminization of governance in determining public expenditure for gender needs. However, it is to be cautioned that even control group methodology should not be infected with problems like sample selection bias and Hawthorne effect (that is, any form of intervention may result in a short-term positive response from the treatment group). Planning and Budgetary Process at Local Level Are there any mechanisms in the local level planning and budgetary systems in Karnataka, which can provide scope to PRIs for catering to spatial gender priorities? It is often noted that although the planning process should ideally start at the gram panchayat level with participation from the gram sabha and the local people, it is usually the gram panchayats themselves who identify and prioritize works to be undertaken. This severely limits the scope of integrating gender needs in the local level planning in Karnataka. Moreover, the resource envelope is drawn based on the resources the panchayat expects to generate and the estimated transfers indicated by the state government. Under the prevailing structure of decentralization in Karnataka, most of the schemes along with the personnel are transferred to the panchayats, though the financial allocation required to implement the schemes is often inadequate. This persistent dearth of funds prevents the local body from initiating plans for suitable public service provision as well as prioritization of existing schemes. As the panchayats receive funds from multiple sources (consolidated funds of the state as well as the central government, various regional development boards and other agencies) there seem to prevail a lack of coordination and transparency in implementation of various schemes which can result in misappropriation and inefficiency. West Bengal The origin of fiscal decentralization in West Bengal may be traced to the late nineteenth century. However, the local bodies enjoyed very limited autonomy and were dominated by rural elites given the property restrictions on franchise. After independence, as per the recommendation of Balwantrai-Mehta Committee (1957), West Bengal Panchayat Act was passed in the same year with the intention to set up a four-tier
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panchayati raj system.35 Subsequently with the enactment of the West Bengal Panchayati Raj Act of 1993, a three-tier system of panchayats was introduced at district, block and village levels. The organization structure of the third tier system in West Bengal comprises 16 zilla parishads, 340 block panchayats and 3314 gram panchayats. The State Finance Commission of West Bengal constituted in aftermath to 73rd Constitutional Amendment recommended the fiscal devolution to the three tiers of PRIs in the ratio of 30:20:50. As mentioned, the fiscal devolution (16 percent of the net proceeds of the own tax revenue of the state government which go as entitlement to the PRIs) is based on two criteria; population and the index of backwardness, giving equal weight to both criteria. It is to be noted here that in order to encourage own revenue initiatives of PRIs, SFC recommended that 2 percent of the entitlement due to a district would be set aside to operate as an incentive fund. The incentive scheme proposed was that any local body raising its own income by 5 percent or more in a financial year should be entitled to a bonus of 2/3 of the incremental revenue. The recommendation of SFC of West Bengal in terms of devolution has considerably reduced adhocism and arbitrariness in the fiscal devolution to the third tier. It guarantees a non -discretionary assured grant for each PRI that could be spent according to the priorities set by themselves, even though the dependence of PRIs on grants would continue in West Bengal. Yet another notable development is that the SFC made it a point that any scheme of devolution of resources from the state level to local bodies should be from the pool of state’s own taxes instead of individual tax-based sharing, since the growth of individual taxes vary considerably from year to year. Planning and Budgetary Process at Local Level With the commencement of SFC, there were significant changes in the planning process at the district level. Earlier, the District Plans consisted mostly of departmental schemes drawn up by the departments, may be with the participation of lower tier officials of the departments, but independently of the elected bodies. The role of the three-tier panchayats in the District Plan largely consisted of utilization of funds provided to them for poverty alleviation programmes or as untied funds. The integration of planning at the district level was more of a formality before the SFC came. The new entitlement scheme recommended by SFC has provided the elected bodies with considerable funds to pursue their own
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priorities through the plans they can draw up. The flexibility of district plans thus increased considerably. The question at this juncture is whether these changes occured in the planning and budgeting process provided any scope for the new EWR to prioritize their gender needs? Chattopadhyay and Duflo (2001) have measured the impact of feminization of governance at local level on the outcomes of decentralization with data collected from a survey of all investments in local public goods made by the village councils in one district in West Bengal. Yet another study in the context of West Bengal on decentralized gender budgeting by UNIFEM, examining the budgetary policies with the broad objective of assessing the extent of efforts put in by the state government towards improving the relative position of women in the state, is mainly confined to state level.36 However, the analysis of local budgets under this UNIFEM study reveals that there is no information about whether or not funds given to local bodies are actually spent or not. It also makes a few reference to the fact that the local bodies are not capable of executing the functions devolved due to low technical capabilities of their staff. The study also shows that schemes are similarly loaded on the local bodies by all superior levels of government without any checks on the technical capability of the local bodies to execute the works. The result is that funds remain unspent and each PRI has a growing opening balance. To conclude, Kerala has shown a good example in integrating both the elements through integrating gender needs in the process of decentralized planning after identifying the gender needs through participatory process through gram sabhas as well as translating it into women component plan in fiscal transfers. In Karnataka, the process of decentralization has created immense scope for incorporating gender needs at local level, though that remains substantially unexplored. In West Bengal, the women in governance at the third tier could change the types of public expenditure at local level more corresponding to the revealed preferences (‘voice’) by women. However, that could have little influence on gender needs as most of the expenditure even at the local level is in the nature of committed non- developmental expenditure.
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Fiscal Decentralization and Local Level Gender Budgeting in Other Countries: Case Studies This section broadly discusses the fiscal decentralization and gender budgeting at the local level of four countries, including Morocco, South Africa, Nepal, and Ethiopia. Morocco Morocco is a constitutional monarchy in North Africa, whose territory encompasses the coastal plain on the Atlantic, desert region of Sahara, and the Atlas mountain ranges. Morocco got independence in 1956 from French rule. It has a population of 30.1 million and the extent of urbanisation is 57 percent. As per recent estimates, the Gender Development Index (GDI) of Morocco is 0.616 as compared to its Human Development Index (HDI) at 0.631. The majority population of the country is Muslim population. It is also a patriarchal society. However, during the last few years there has been a significant attempt to change the status of women and considerable efforts have been made to incorporate mainstream gender in socio-economic policies, including gender budgeting initiatives. The decentralization process in Morocco dates back to the 1960 charter, when the charter was issued recognizing the need for local governments. Though limited in scope, the charter helped to constitute the local governments. However, it was the 1976 charter which started the real decentralization process. It enshrined “communes”, the level of government closest to the people, as the core of local democracy and they were assigned a role in economic and social development. With this, the local government structure comprised of provinces and prefectures and urban and rural communes. A new tier “Region” was created in 1992 and since has a regional assembly. With the adoption of the 1997 charter, this new tier was assigned with the main objective of consolidating and coordinating the efforts of the provinces particularly in planning and land use development. The constitutional reforms in 1986 and 1992 empowered the subnational governments to exercise a number of legislative and administrative powers. The New Communal Charter, 2001 (enacted in 2003) expanded the powers of elected representatives to carry out local development particularly to rural communes, control budgets, and impose local taxes. This also attempted to enhance their financial powers
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and enabled greater participation of citizens in the public service provision. Thus, the local government structure in Morocco below the central level comprises 16 regions, 42 provinces, and 28 prefectures, 249 urban communes and 1298 rural communes. The national (central) government has two chambers namely, the House of Representatives and the Upper House represented by Unions, Chambers of Commerce and representatives of local governments (Mayors). The proportion of local government representatives in the Upper House is much larger than others. In the House of Representatives, 10 percent of seats are reserved for women. The legislative body for the Regional Council is elected through the electoral college and the executive head of the Region, Wali, is appointed by the Dahir (royal decree) from among the governors of the prefectures or provinces within the region. The provincial or prefectoral assembly is elected indirectly by the communal councillors and colleges of professional chambers and the governor is the executive head, appointed by the Dahir. The legislative body for the communes are the communal councils and the members of the council are directly elected by a universal suffrage. The President of the communal council is elected by the elected members of the council from among themselves. Thus, ever since 1976, when communes were formed, they constitute the basic democratic institution of decentralization. The communes are considered “core of local democracy” and are basic governmental units closest to the people. They have been assigned the responsibility of providing basic services such as providing basic infrastructure, solid waste management, transport development and preservation of markets, and public lighting. Provision of other important public services including some of the social services such as health care and hospital services, and education are still with the central government. Local governments get their resources for spending from their own revenues, devolved taxes from the central government and have recourse, to some extra-budgetary resources including loans. There are 42 taxes assigned to the local governments and most of these are collected by the communes. In terms of fiscal importance, the locally raised revenues are not important. Together, these constitute less than 5 percent of total receipts of the local governments. The regions get one percent of corporate tax and individual income tax for meeting their 6 expenditures which, in the main, consists of coordination of the activities of provinces and prefectures. The provinces, prefectures, and communes receive 30 percent of the value added taxes (VAT) collections. Of the shareable proceeds, provinces and prefectures receive 40 percent of the
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shareable proceeds, the share of urban communes is 24 percent and the rural communes receive 26 percent. There are conditions on the spending of devolved tax revenues. It is stipulated that 8 percent of the proceeds should be spent on “public goods” which benefit all citizens equally, 79 percent should be spent on meeting operational expenditures and remaining 13 percent should be spent on investment expenditures. The lump sum component of distributable VAT revenues is distributed on the basis of the ratio of personnel expenditures. The operational component among the provinces is distributed on the basis of two indicators, population and the area in the ratio two-thirds, and one-third. The distribution of operational expenditures among communes is done on the basis of tax effort. Investment component is distributed on the basis of the nature of the projects. Thus, although attempt has been made to make the distribution formula based and transparent, there are opaque and discretionary elements in the transfer system. The Ministry of Interior is responsible for the administration, supervision, and coordination of local governments. The fiscal year is the calendar year. The budget cycle for the local governments begins with the guidelines issued by the Ministry of Interior in October setting out the basic ground rules for preparing revenue and expenditure. For all levels except rural communes, the local budgets prepared by respective levels of governments are sent to the Ministry of Interior after being duly approved by the respective Councils. In the case of rural communes, the approval has to be obtained from the governor of the province. After approval, these are sent to the Ministry of Finance for coordination. Despite initiatives taken to decentralize administration, Morocco has a highly centralized fiscal system. Together, all local governments incur a little over 13 percent of total expenditures or about 3.5 percent of GDP. Of this overwhelming proportion is financed through transfers from above by way of shared taxes. The share of VAT transfers alone constitutes almost 50 percent of the total current and capital receipts. Despite these significant features of decentralization, it is important to note that the fiscal system in Morocco is that local governments have very limited role. Even though there has been formal devolution of functions to the local bodies in Morocco in the backdrop of the New Communal Charter, elements of centralization are evident as local governments remain under the supervision of Ministry of Interior. The level of spending by the local governments is so low that they cannot make much difference to providing access, ensuring entitlements or enabling empowerment of women, however well disposed
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they are, towards achieving gender equality and mainstreaming women in organized economic activities. Nor is the sensitivity to gender issues in Morocco at the local level high enough to make significant difference to improve equality. There is no systematic attempt to mainstream gender approach in local budgets. There is no strategic planning to sensitize and educate the policymakers on gender equality. The stakeholders of local governments too are not well informed about the issues of gender sensitivity to make any significant impact on policies. Given the traditional nature of society with significant gender inequality, the approach continues to confine women to traditional roles. There is an initiative to analyze the local budgetary process, planning and implementation on the one hand, and the extent of gender equality accomplished in them in the 5 communes to initiate gender sensitive analysis of local budgets and assess the potential of gender mainstreaming in the local budgetary process on the other. The five communes included for the study are, Casablanca city council and urban commune of Sidi Moumen, one urban and rural commune each in Essaouira, a rural commune of Mohemmadia and rural commune of Zagora, which led to help the stakeholders of these communes to develop budget engendering strategies in them. South Africa South Africa has done the analysis of engendering the fiscal policy as an outside government initiative. Launched in 1995, it was the initiative of the post-apartheid regime, which took over the administration of the country in 1994. What distinguishes South African gender budgeting from that of other countries is the interface between racial discrimination and gender inequalities. Understandably, race constitutes an important focus of attention in the policy arena in a country, where 79 percent of the 46.9 million people are Africans. Public policy on gender cannot be built on the homogeneity assumption that all women are equal especially in a country where the overwhelming majority of the female population is African. It was felt that the dimension of race had to be recognized in gender budgeting as well, otherwise the main victims of oppression and discrimination viz., black women did not benefit to any appreciable extent. Thus emphasis moved away from the narrowly conceived gender budgeting with emphasis on budget allocations for women at the national level to affirmative actions through legislation to end discrimination against the blacks in general with special attention to women.
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Further, allocations in public expenditure having potential for benefiting women were sought to be provided more at levels of government closer to the people i.e., through decentralization. In all these initiatives, gender figured as the focus of attention with race. Gender budget initiatives began in South Africa, immediately after the Beijing UN Conference on Women, 1995 as a collaborative venture of women parliamentarians and non-governmental organizations, known as Women’s Budget Initiative (WBI). WBI emphasized that the solution to gender discrimination is mainstreaming gender issues rather than implementing separate women’s programmes and policies. It is to be noted that mainstreaming gender in budget is comparatively a better approach rather than quota-based gender budgeting (of earmarking a specific proportion of each sectoral budget for women, as in the case of Philippines), which is confined to a very negligible part of the budget. Further, gender budgeting initiatives in South Africa focused more on reprioritisation of programmes rather than increasing the budgetary allocation for women. This is against the backdrop of Growth, Employment and Redistribution (GEAR) macropolicy in 1997, which emphasized the hard budget constraints. Moreover, though the environment was more favourable towards gender equality with the adoption of the final constitution in South Africa in 5 1997 as also the development of machinery to oversee implementation of measures with gender focus, such as Office of Status of Women (OSW) and Commission of Gender Equality (CGE), the gender focal points created within the government were engaged more in redressing gender imbalances among the elite of the civil service rather than attending to the needs of poor and needy women. However, the advantage of civil society (outside government) initiative of WBI in South Africa is the participatory, grassroot initiatives by the civil society to provide economic literacy among ordinary people and demystify budgets through the publication of simple budget (sectoral) booklets through a gender lens. The drawback of the WBI is that it failed to institutionalize gender budget within government in South Africa. The sustainability of gender budgeting initiatives in South Africa will depend to a great extent in creating a synergy between civil society and government, in particular with experts in the budget division of Department of Finance to strengthen the public finance lens of gender budgeting. A within government initiative on gender budgeting began in 1998 with the establishment of a women’s pilot budget within Department of Finance. However, this was primarily a donor-driven initiative by the Commonwealth Secretariat, which lasted for only two years. This
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resulted in the inclusion of certain case studies of gender issues within the compilation of sectoral reports tabled on Budget Day in 1999. Since 1999, the initiative has been discontinued by the Department of Finance. However, in the absence of any study in this regard, what has been the impact of these initiatives in terms of gender indicators is not known. WBI took the gender budgeting initiatives to local level for the first time in 1999, though local governments were then in transition in terms of realigning the country from the racially segregated units of the apartheid regime. This was more challenging because of the difficulty in analyzing the local government budgets through a gender lens as most local government services were directed to the households and not women members of households, as such. WBI tended to focus on the poor and the way local government budgets impacted them. Revenue decentralization was one of the core thrusts of WBI in the following two years as attention was drawn to the issues related to fiscal autonomy at subnational levels. However, the within government initiative at local government on gender budgeting is almost invisible in South Africa, except in the province of Gauteng. An attempt was made in Gauteng to incorporate gender elements in its budget to which we turn in the section on budgetary process. As mentioned, though there are no direct initiatives on gender budgeting within government at the national level, several windows have been opened for affirmative action in South Africa in terms of gender, especially through legislations like the Employment Equity Act, Promotion of Equality Act, and Black Economic Empowerment Act (BEE). The Employment Equity Act, 1998 envisages non-discrimination coupled with positive measures of discrimination to accelerate women’s access to employment opportunities and benefits. The provisions of this Act envisage enforcement through the labour court system, labour inspections, and broad monitoring by a statutory body, viz., Commission of Employment Equity (CEE). The Act also addresses issues such as pregnancy discrimination, sexual and other forms of harassment, discrimination on grounds of HIV and AIDS status, discrimination on grounds of family responsibility, pregnancy discrimination, and discrimination on grounds of disability, including failure to provide reasonable accommodation, as per Beijing Plus Ten Report, South Africa, 2005. The Promotion of Equality and Prevention of Unfair Discrimination Act, 2000, provides a comprehensive legal framework for the prohibition of discrimination, redressal for discrimination, progressive eradication of discrimination, and promotion of equality. The core of enforcement mechanism has the
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specialized equality courts. At least 60 equality courts have been established to provide relief to claimants in magistrate courts throughout the country. The government has made a conscious decision to prioritize the advancement of women along with people with disabilities, workers, and rural communities in programmes or activities that are designed to undo the legacy of apartheid in the matter of participation by the black community in the economy. This policy commitment is reflected in the key national instruments that regulate BEE. These include the Broad-based BEE, 2003 (Act 53 of 2003), and the Draft codes of Good Practice on BEE. The National Policy Framework on Gender Equality and Women’s Empowerment mandates the establishment of a regular monitoring mechanism through JMC (Joint Monitoring Committee) of Parliament to ensure that gender considerations are included in all legislations. Despite these legislations and affirmative actions, within each racial group, inequalities persisted significantly. An important dimension of the interface between racial discrimination and gender inequalities in South Africa has been intra-racial income inequalities. If we decompose inequality into within-group and between-group components using the Theil-T, empirical evidence showed that 40.7 percent of inequality is owing to between-race inequality, 33 percent on account of intra-African inequality and 21 percent due to intra-White inequality (Ingrid, 2002). The point to be noted here is that affirmative action in South Africa continues to be shaped solely around racial identities, which ignores intra-racial inequalities, which is one of the emerging criteria of social differentiation in the country. In spite of the Employment Equity Act, which is aimed at improving prospects for historically disadvantaged employees, black women continue to face economic disadvantage. Labour Force Survey (2003) revealed that African women faced high rates of unemployment compared to other groups and especially in comparison to white men and women. Effective fiscal decentralization has a significant role to play in improving the access of women to the basic infrastructure and public service delivery. At the subnational level, with increasing decentralization, there is good scope for initiatives on gender budgeting; the rationale being that merit goods like education and health are the responsibility of provincial government and the provisioning of quasipublic goods like, water supply which is of crucial importance for women, is the responsibility of local governments. However, there is no meaningful decentralization at the provincial level, as the revenue powers of provinces are negligible.
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Ethiopia Ethiopia is in the process of integrating gender in intergovernmental fiscal transfers. In Ethiopia, the process has been initiated by the House of Federations (Senate) and the Terms of Reference (TOR) were moved in Parliament for public hearing. Subsequently, a majority was secured in the Senate for gender-integrated TOR and the “proclamation” by the Senate to make it a reality in their forthcoming Fiscal Commission is awaited. NIPFP, India is working in close association with House of Federation (Senate), Government of Ethiopia, and the Forum of Federation in this process of integrating gender in fiscal transfers in Ethiopia. Nepal In the fiscal year 2007–2008, the Ministry of Finance, Government of Nepal introduced gender budgeting. A new classification of budgetary transactions was introduced to incorporate gender budgeting into the budget. Like that of India, Bangladesh, and Sri Lanka, the new classification mainly entailed categorizing public expenditure by benefits to women. According to the government’s guidelines, all line ministries, departments, project/programme units at all levels have to provide information classifying their demands for grants (on new preprograms and associated expenditure items) into the three categories, directly genderresponsive (G01), indirectly gender-responsive (G2) and neutral, scoring as per the indicators. Public budget expenditures are classified into three categories: (i) Those that are more than half related to programmes directly responsive to gender (>50 percent); (ii) Those that are indirectly gender-responsive (>20 to < 50 percent) and (iii) Those that are neutral. The scoring system takes account of different aspects of gender sensitivity, participation, capacity building, benefit sharing, and increased access to employment and income-earning opportunities and reduction in women’s work load. These indicators have been allocated 20 potential percentage points each. Programmes scoring 50 percent or more are classified as directly supportive to women, those scoring 20–50 percent as indirectly supportive and scoring less than 20 percent as neutral, as per the Ministry of Finance, Government of Nepal, 2007. The complexity and subjectivity of the scoring method of gender budgeting may one of the reasons for the lack of universal acceptance of Nepal’s experience with gender budgeting.
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In the fiscal year 2007–2008, the Ministry of Finance, Government of Nepal introduced gender budgeting. A new classification of budgetary transactions was introduced to incorporate gender budgeting into the budget. Like that of India, Bangladesh and Sri Lanka, the new classification mainly entailed categorizing public expenditure by benefits to women. According to the government’s guidelines, all line ministries, departments, project/programme units at all levels have to provide information classifying their demands for grants (on new preprograms and associated expenditure items) into the three categories, directly gender responsive (G01), indirectly gender responsive (G2) and neutral, scoring as per the indicators. The gender budgeting classification criteria and corresponding scores are given in Table 6.1. Public budget expenditures are classified into three categories: ● Those that are more than half related to programmes directly responsive to gender (>50 percent) ● Those that are indirectly gender-responsive (>20 to < 50 percent) ● Those that are neutral (